Subjects -> MANUFACTURING AND TECHNOLOGY (Total: 363 journals)
    - CERAMICS, GLASS AND POTTERY (31 journals)
    - MACHINERY (34 journals)
    - MANUFACTURING AND TECHNOLOGY (223 journals)
    - METROLOGY AND STANDARDIZATION (6 journals)
    - PACKAGING (19 journals)
    - PAINTS AND PROTECTIVE COATINGS (4 journals)
    - PLASTICS (42 journals)
    - RUBBER (4 journals)

MACHINERY (34 journals)

Showing 1 - 27 of 27 Journals sorted alphabetically
Acta Mechanica Solida Sinica     Hybrid Journal   (Followers: 8)
Advanced Energy Materials     Hybrid Journal   (Followers: 31)
Applied Mechanics Reviews     Full-text available via subscription   (Followers: 27)
CORROSION     Full-text available via subscription   (Followers: 20)
Electric Power Components and Systems     Hybrid Journal   (Followers: 7)
Foundations and TrendsĀ® in Electronic Design Automation     Full-text available via subscription   (Followers: 1)
International Journal of Machine Tools and Manufacture     Hybrid Journal   (Followers: 8)
International Journal of Machining and Machinability of Materials     Hybrid Journal   (Followers: 4)
International Journal of Manufacturing Technology and Management     Hybrid Journal   (Followers: 8)
International Journal of Precision Technology     Hybrid Journal   (Followers: 1)
International Journal of Rapid Manufacturing     Hybrid Journal   (Followers: 3)
International Journal of Rotating Machinery     Open Access   (Followers: 2)
Journal of Machinery Manufacture and Reliability     Hybrid Journal   (Followers: 2)
Journal of Manufacturing and Materials Processing     Open Access  
Journal of Mechanics     Hybrid Journal   (Followers: 9)
Journal of Strain Analysis for Engineering Design     Hybrid Journal   (Followers: 5)
Journal of Terramechanics     Hybrid Journal   (Followers: 4)
Machine Design     Partially Free   (Followers: 183)
Machine Learning and Knowledge Extraction     Open Access   (Followers: 12)
Machines     Open Access   (Followers: 4)
Materials     Open Access   (Followers: 4)
Mechanics Based Design of Structures and Machines: An International Journal     Hybrid Journal   (Followers: 8)
Micromachines     Open Access   (Followers: 2)
Pump Industry Analyst     Full-text available via subscription   (Followers: 1)
Russian Engineering Research     Hybrid Journal  
Sensor Review     Hybrid Journal   (Followers: 2)
Surface Engineering and Applied Electrochemistry     Hybrid Journal   (Followers: 6)
Similar Journals
Journal Cover
Machines
Number of Followers: 4  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2075-1702
Published by MDPI Homepage  [84 journals]
  • Machines, Vol. 10, Pages 286: Rendering Natural Bokeh Effects Based on
           Depth Estimation to Improve the Aesthetic Ability of Machine Vision

    • Authors: Fan Wang, Yingjie Zhang, Yibo Ai, Weidong Zhang
      First page: 286
      Abstract: Machine vision is the key to realizing computer-vision tasks such as human–computer interaction and autonomous driving. However, human perception of an image’s beauty is innate. If a machine can increase aesthetic awareness, it will greatly improve the comfort of human perception in human–computer interaction. The bokeh effect is one of the most important ways to improve the artistic beauty of photographic images and the image aesthetic quality. Bokeh rendering of an image can highlight the main object of the image and blur unnecessary or unattractive background details. The existing methods usually have unrealistic rendering effects with obvious artifacts around the foreground boundary. Therefore, we propose a natural bokeh-rendering method based on depth estimation that satisfies the following characteristics: objects in the focal plane are clear and out-of-focus objects are blurred; and the further away from the focal plane, the more blurred the objects are. Our method consists of three modules: depth estimation, background subdivision, and bokeh rendering. The background-subdivision module can select different focal planes to obtain different blur radii, making the bokeh-rendering effect more diverse, so that it does not oversegment objects. The bokeh-rendering module adjusts the degree of bokeh by adjusting the blur-radius factor. In the experimental section, we analyze the model results and present the visualization results.
      Citation: Machines
      PubDate: 2022-04-19
      DOI: 10.3390/machines10050286
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 287: Analysis of the Implementation of the Single
           Minute Exchange of Die Methodology in an Agroindustry through Action
           Research

    • Authors: Murilo Augusto Silva Ribeiro, Ana Carolina Oliveira Santos, Gabriela da Fonseca de Amorim, Carlos Henrique de Oliveira, Rodrigo Aparecido da Silva Braga, Roberto Silva Netto
      First page: 287
      Abstract: This work aims to implement and analyze the effect of the Single Minute Exchange of Die (SMED) implementation in the bean packaging operation in a company in east Minas Gerais, Brazil. Design/Methodology/Approach: The research methodology used was action research. Two cycles of action research were conducted; the first to carry out phase one of SMED, and the second to execute phases two and three. Originality/Research gap: There are few studies on the application of Lean Manufacturing tools in agroindustry. Some works present case studies, mainly in the food supply chain aiming to fill this gap. Regarding SMED applied in agribusiness, no work was found. Key statistical results: The implementation of this methodology allowed the reduction of setup time by around 58%, the distance travelled by operators in the process by approximately 50%, in addition to gains in a production capacity of 14%. Practical Implications: It is concluded that the application of the methodology caused an increase in the company’s productivity, as it was possible to obtain gains in productive capacity without changing the amount of hours worked or the number of employees involved in the production process. Limitations of the investigation: This methodology was applied only once and the challenges encountered were not documented.
      Citation: Machines
      PubDate: 2022-04-20
      DOI: 10.3390/machines10050287
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 288: Increasing Machining Accuracy Based on CNC
           Machine Tool Correction Data by Using Ad Hoc Modification

    • Authors: Švéda, Chládek, Hornych, Kozlok, Smolík
      First page: 288
      Abstract: The geometric accuracy of a workpiece represents one of the key parameters defining its quality, and it is affected by the appropriate selection of the machine tool, control system, NC program and cutting conditions. Up-to-date control systems contain advanced compensation functions, which increase the volumetric accuracy of the machine tools. Nevertheless, these functions use correction data measurements within the machine tool’s periodic maintenance plan. This paper introduces a method for ad hoc correction data modification. This modification is based on the difference between the real and nominal workpiece geometries, which are evaluated on a coordinate-measuring machine as a standard process in high-accuracy workpiece production. Correction data are compiled in the form of a three-dimensional structured mesh, where nodes of the mesh contain such correction values that interpolations within the mesh suppress workpiece geometric deviations. The correction mesh calculations are based on the assumption that the nodes are connected by imaginary springs and that they are initially in force equilibrium. Force disbalance is introduced by workpiece geometric deviations evaluated at arbitrary points. Then the new position of force-balanced nodes is calculated. Experimental results on a three-axis machining center have verified the proposed method, where geometric accuracy of the workpiece increased more than 85% without any negative effect on surface quality. The approach presented is efficient for increasing workpiece accuracy without the need for NC program modification.
      Citation: Machines
      PubDate: 2022-04-20
      DOI: 10.3390/machines10050288
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 289: Practical Obstacle-Overcoming Robot with a
           Heterogeneous Sensing System: Design and Experiments

    • Authors: Yuanhao Huang, Ruifeng Meng, Jingyang Yu, Ziqi Zhao, Xinyu Zhang
      First page: 289
      Abstract: It is challenging for robots to improve their ability to pass through unstructured environments while maximizing motion performance in cities and factories. This paper presents an omnidirectional deformable wheeled robot based on a heterogeneous sensing system. We presented a novel structure with dual swing arms and six wheels. Moreover, the heterogeneous sensing system can perceive critical environmental data, such as friction and temperature, to assist the robot in executing different functions. In addition, a top-down ‘Order–Decision–Behaviour’ overall motion strategy is proposed based on the data acquisition. The strategy combines the key condition parameters with a kinetic model to integrate the robot’s movement, overcoming of obstacles, and mode switching. The robot is flexible and fast in moving mode and can overcome obstacles safely, reliably, and simply. This study describes the robot’s design, strategy, simulation, and experiments. Motion performance and strategy were investigated and evaluated in field environments.
      Citation: Machines
      PubDate: 2022-04-21
      DOI: 10.3390/machines10050289
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 290: Developing a Novel Fully Automated Concept
           to Produce Bowden Cables for the Automotive Industry

    • Authors: Vitor Fernando Crespim Sousa, Francisco José Gomes da Silva, Raul Duarte Salgueiral Gomes Campilho, Arnaldo Guedes Pinto, Luís Pinto Ferreira, Nuno Martins
      First page: 290
      Abstract: The automotive industry is one of the driving forces of the global industry; thus, it is a very competitive sector which creates a constant need for process improvement, regarding productivity, quality, and flexibility. Automation has proven to be a viable solution for these production problems, with the rising adoption of these automated system by companies that try to design and implement more flexible systems, while reducing costs and improving process quality. Furthermore, the use of automation reduces the manpower factor and its associated variability. In the present work, a new concept for a Bowden cable production process is presented by employing the design science research (DSR) methodology. The project starts with the analysis of the previous production concept, determining possible problems and improvements, as well as setting objectives/requirements for a possible new concept/equipment. This information was used to develop a new automated Bowden cable production equipment, implementing several changes to the old concept and filling a gap in the literature in this field. The developed system was implemented and tested. A considerable reduction in cycle time was registered by 25%, which resulted in an increase of 30% in process productivity.
      Citation: Machines
      PubDate: 2022-04-21
      DOI: 10.3390/machines10050290
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 291: Assembly of Compliant Structures with
           Autonomous Industrial Mobile Manipulators (AIMM) Using an End Effector
           with Active Deformation Compensation for the Assembly of Flaps

    • Authors: Maximilian Neitmann, Tom Rothe, Erik Kappel, Christian Hühne
      First page: 291
      Abstract: Composite structures in aeroplanes are often thin-walled and lightweight, resulting in significant compliance, which presents a handling and assembly challenge due to the associated part deformations. In order to counteract these deformations, the parts are held in their specified geometry using stiff and correspondingly heavy fixtures or jigs. Mobile industrial robots are very versatile and widely used in industrial volume production, but they are limited in their payload capacity. High-rate production of large aerospace modules requires highly automated flexible assembly processes. The approach presented in this paper is to combine mobile units with lightweight assembly jigs that have the capability of deformation compensation. The subject of the study is a high-rate assembly process for flap modules using an Autonomous Industrial Mobile Manipulator (AIMM) and a lightweight end effector. The end effector has a shape compensation function, implemented by an integrated Stewart platform, which enables the compensation of manufacturing tolerances as well as gravity effects. The compensation function is used in a closed loop and counteracts shape deviations by appropriate fixture shape adjustments. The paper reports on the conceptual design of the assembly scenario, the design of the end effector, its realization and the successful experimental demonstration at 1:1 scale.
      Citation: Machines
      PubDate: 2022-04-21
      DOI: 10.3390/machines10050291
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 292: A New Trajectory Tracking Control Method for
           Fully Electrically Driven Quadruped Robot

    • Authors: Yulong You, Zhong Yang, Teng’an Zou, Yaoyu Sui, Changliang Xu, Chi Zhang, Hao Xu, Zhao Zhang, Jiaming Han
      First page: 292
      Abstract: To improve the accuracy of tracking the trunk center-of-mass (CoM) trajectory and foot-end trajectory in a fully electrically driven quadruped robot, an efficient and practical new trajectory tracking control method is designed. The proposed trajectory tracking method is mainly divided into trunk balance controller (TBC) and swing leg controller (SLC). In TBC, a quadruped robot dynamics model is developed to find the optimal foot-end force that follows the trunk CoM trajectory based on the model predictive control (MPC) principle. In SLC, the Bessel curve is planned as the desired trajectory at the foot-end, while the desired trajectory is tracked by a virtual spring-damping element driving the foot-end, meanwhile, the radial basis function neural network (RBFNN) is applied for supervisory control to improve the control performance for the system. The experimental results show that the control method can modify the robot’s foot-end trajectory tracking effect, so that the stability error can be eliminated and the robustness of the controller can be improved, meanwhile, the linear and circular trajectory for CoM can be tracked accurately and quickly.
      Citation: Machines
      PubDate: 2022-04-21
      DOI: 10.3390/machines10050292
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 293: Assessing the Effect of Interimplant
           Distance and Angle on Different Impression Techniques

    • Authors: Berkman Albayrak, İsmail Hakkı Korkmaz, Alvin G. Wee, Cortino Sukotjo, Funda Bayındır
      First page: 293
      Abstract: We aimed to evaluate the trueness of digital and conventional impression techniques based on different angles and distances between implants and the deviation caused by the angle and distance parameters varying between implants. Eight implants were placed in a polyurethane edentulous mandibular model at different angles and distances. After obtaining a 3-dimensional (3D) reference model by using an optical scanner, the model was scanned with three intraoral scanners: Cerec Omnicam (DO), Trios 3 (DT), and Carestream 3500 (DC). Then, the master casts obtained from the conventional impressions (C) were also digitized, and all impression data were imported into reverse engineering software to be compared with the 3D reference model. Distance and angle measurements between adjacent implants were performed, and the data were analyzed with ANOVA–Tukey and Kruskal Wallis tests. The significance level was accepted as p < 0.05. While DT and C groups gave the best results for high interimplant distances, the trueness of intraoral scanners was found to be superior to the conventional method between closer implants. At higher angulations, the angular trueness of C group was found to be significantly lower. At short distances, digital groups showed superiority, and the trueness of conventional impression decreased with higher angulations.
      Citation: Machines
      PubDate: 2022-04-21
      DOI: 10.3390/machines10050293
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 294: YOLO-GD: A Deep Learning-Based Object
           Detection Algorithm for Empty-Dish Recycling Robots

    • Authors: Xuebin Yue, Hengyi Li, Masao Shimizu, Sadao Kawamura, Lin Meng
      First page: 294
      Abstract: Due to the workforce shortage caused by the declining birth rate and aging population, robotics is one of the solutions to replace humans and overcome this urgent problem. This paper introduces a deep learning-based object detection algorithm for empty-dish recycling robots to automatically recycle dishes in restaurants and canteens, etc. In detail, a lightweight object detection model YOLO-GD (Ghost Net and Depthwise convolution) is proposed for detecting dishes in images such as cups, chopsticks, bowls, towels, etc., and an image processing-based catch point calculation is designed for extracting the catch point coordinates of the different-type dishes. The coordinates are used to recycle the target dishes by controlling the robot arm. Jetson Nano is equipped on the robot as a computer module, and the YOLO-GD model is also quantized by TensorRT for improving the performance. The experimental results demonstrate that the YOLO-GD model is only 1/5 size of the state-of-the-art model YOLOv4, and the mAP of YOLO-GD achieves 97.38%, 3.41% higher than YOLOv4. After quantization, the YOLO-GD model decreases the inference time per image from 207.92 ms to 32.75 ms, and the mAP is 97.42%, which is slightly higher than the model without quantization. Through the proposed image processing method, the catch points of various types of dishes are effectively extracted. The functions of empty-dish recycling are realized and will lead to further development toward practical use.
      Citation: Machines
      PubDate: 2022-04-22
      DOI: 10.3390/machines10050294
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 295: Imbalanced Fault Diagnosis of Rolling
           Bearing Using Data Synthesis Based on Multi-Resolution Fusion Generative
           Adversarial Networks

    • Authors: Chuanzhu Hao, Junrong Du, Haoran Liang
      First page: 295
      Abstract: Fault diagnosis of industrial bearings plays an invaluable role in the health monitoring of rotating machinery. In practice, there is far more normal data than faulty data, so the data usually exhibit a highly skewed class distribution. Algorithms developed using unbalanced datasets will suffer from severe model bias, reducing the accuracy and stability of the classification algorithm. To address these issues, a novel Multi-resolution Fusion Generative Adversarial Network (MFGAN) is proposed for the imbalanced fault diagnosis of rolling bearings via data augmentation. In the data-generation process, the improved feature transfer-based generator receives normal data as input to better learn the fault features, mapping the normal data into fault data space instead of random data space. A multi-scale ensemble discriminator architecture is designed to replace original single discriminator structure in the discriminative process, and multi-scale features are learned via ensemble discriminators. Finally, the proposed framework is validated on the public bearing dataset from Case Western Reserve University (CWRU), and experimental results show the superiority of our method.
      Citation: Machines
      PubDate: 2022-04-22
      DOI: 10.3390/machines10050295
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 296: Add-On Type Data-Driven Ripple-Free
           Dual-Rate Control Design Based on the Null Space of Steady-State Step
           Responses

    • Authors: Takao Sato, Ryota Yasui, Natsuki Kawaguchi
      First page: 296
      Abstract: In the present study, a data-driven ripple-free design is proposed for a dual-rate sampled-data control system in which the sampling interval of the plant output is longer than the holding interval of the control input. The objective of the present study is to improve the steady-state intersample response without changing the sampled response and without using the plant model. To achieve the objective directly from controlled data, an add-on input based on the null space of steady-state step responses to an existing control system is used. The open-loop or closed-loop system to obtain the step response is assumed to be stable. In the present study, a two-degree-of-freedom design is given that redesigns the intersample output response independently of the steady-state sampled output response. In a numerical example, the proposed method is applied to a linear time-invariant single-input single-output stable system, where intersample ripples are eliminated using the add-on input that is independent of the existing sample output response in steady state.
      Citation: Machines
      PubDate: 2022-04-22
      DOI: 10.3390/machines10050296
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 297: Optimization and Realization of the
           Coordination Control Strategy for Extended Range Electric Vehicle

    • Authors: Keqin Zhao, Diming Lou, Yunhua Zhang, Liang Fang
      First page: 297
      Abstract: This paper designed a fuzzy adaptive proportional integral differential (PID) control algorithm to optimize the overshoot of speed and torque, fuel consumption and exhaust emissions of the traditional PID control strategy in the process of working condition switching of an extended range electric vehicle. The simulation was carried out in Matlab/Simulink, and the optimization of the control strategy was verified by a bench test. The results show that the fuzzy adaptive PID control strategy effectively reduced the speed overshoot in the process of working condition switching compared with the traditional PID control strategy. The bench test proved that the fuzzy adaptive PID control strategy could effectively optimize the switching process, especially in the speed and torque reduction switching process, and the speed overshoot rate of the fuzzy PID control was greatly reduced to 0.7%, far less than that of the traditional PID control with 6.6%, while the torque overshoot rate was within 0.8%. Additionally, the fuzzy adaptive PID control could effectively reduce the fuel consumption, especially in the switching process of increasing the speed and torque, where the fuel consumption of the fuzzy adaptive PID control was 2.1% and 0.5% lower than that of the traditional PID control, respectively. Additionally, the fuzzy adaptive PID control could also reduce the particulate emissions, especially in the process of increasing the speed and torque, where the number of particles of the fuzzy PID control was 11% and 19% less than that of the traditional PID control, respectively. However, the NOx emissions based on the fuzzy PID control were slightly higher than those of the traditional PID control due to the smooth operation and improved combustion.
      Citation: Machines
      PubDate: 2022-04-22
      DOI: 10.3390/machines10050297
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 298: Influence of Fit Clearance and Tightening
           Torque on Contact Characteristics of Spindle–Grinding Wheel Flange
           Interface

    • Authors: Qianqian Yuan, Yongsheng Zhu, Ke Yan, Xinzhuo Zhang
      First page: 298
      Abstract: The spindle and grinding wheel flange (GWF) adopt double positioning of a tapered surface and end face. Due to the processing quality, the contact state of the spindle–GWF interface cannot be determined accurately. Based on the theory of finite element and the Yoshimura integral method, an analysis method for the contact stiffness of the spindle–GWF interface was established. In addition, the effects of the spindle–GWF interface’s original clearance and tightening torque on the contact pressure, final contact state and contact stiffness of the spindle–GWF interface were investigated and experimentally verified. It was found that the final contact state of the spindle–GWF changed when the tightening torque increased, especially when the original contact state was tapered contact, and the final contact state changed significantly after assembly. The contact pressure and contact stiffness of the spindle–GWF interface are increased by increasing the tightening torque. The radial stiffness is more affected by the end clearance variation compared to the axial and angular stiffness. When the original contact state is tapered contact, the radial stiffness of the interface is at maximum in three contact states. This research provides theoretical guidance for GWF assembly on gear-grinding machines.
      Citation: Machines
      PubDate: 2022-04-22
      DOI: 10.3390/machines10050298
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 299: Simulation of the Landing Buffer of a
           Three-Legged Jumping Robot

    • Authors: Yilin Yan, Katharine Smith, Alejandro Macario-Rojas, Hongbo Zhang
      First page: 299
      Abstract: In recent years, the research of planetary exploration robots has become an active field. The jumping robot has become a hot spot in this field. This paper presents a work modelling and simulating a three-legged jumping robot, which has a powerful force, high leaping performance, and good flexibility. In particular, the jumping of the robot was simulated and the landing buffer of the robot was analyzed. Because this jumping robot lacks landing buffer, this paper verifies a method of absorbing landing kinetic energy to improve landing stability and storing it as the energy for the next jump in the simulation. Through the landing simulation, the factors affecting the landing energy absorption are identified. Moreover, the simulation experiment verifies that the application of the intermediate axis theorem helps to absorb more energy and adjust the landing attitude of the robot. The simulation results in this paper can be applied to the optimal design of robot prototypes and provide a theoretical basis for subsequent research.
      Citation: Machines
      PubDate: 2022-04-23
      DOI: 10.3390/machines10050299
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 300: Investigation of the Effect of Rope Cutter
           on Water Flow behind Ship Propellers Based on CFD Analysis

    • Authors: Antony John Nyongesa, Van Chien Pham, Sung Hwan Yoon, Woo-Seok Kwon, Jun-Soo Kim, Duy Nam Ngo, Jae-Hyuk Choi, Young-Yun Sul, Won-Ju Lee
      First page: 300
      Abstract: Small vessels operating in coastal waters are susceptible to propeller failure because of the entanglement of marine debris. Secondary accidents such as the injury of divers may also occur when removing entangling material. Rope cutters are devices used to prevent marine litter from entangling the propeller of small ships. However, installing rope cutters on propeller shafts might affect the working of the propeller. In this study, three-dimensional simulations were performed to investigate the effect of a rope cutter on flow characteristics behind the propeller. The Computational fluid dynamics (CFD) models were validated by particle image velocimetry (PIV) experiments performed in a rope cutter performance testing tank. The study results showed that the installation of a rope cutter on the propeller shaft led to an insignificant reduction in water flow velocity magnitude behind the propeller. Additionally, the effects of the rope cutter on the reductions of thrust (0.87%) and torque (0.76%) of the propeller were also negligible. However, it is very interesting to note that rope cutter installation resulted in a lower vortex formation, leading to a significant reduction in the turbulence intensity behind the propeller by 27.12%, 37.50%, and 47.29% at 100, 150, and 200 rpm propeller speed, respectively. Based on the study results, it can be concluded that rope cutters help to reduce propeller entanglements without significantly affecting the propeller’s working.
      Citation: Machines
      PubDate: 2022-04-23
      DOI: 10.3390/machines10050300
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 301: Design and Characterization of a
           Rolling-Contact Involute Joint and Its Applications in Finger Exoskeletons
           

    • Authors: Renghao Liang, Guanghua Xu, Qiuxiang Zhang, Kaiyuan Jiang, Min Li, Bo He
      First page: 301
      Abstract: The hand exoskeleton has been widely studied in the fields of hand rehabilitation and grasping assistance tasks. Current hand exoskeletons face challenges in combining a user-friendly design with a lightweight structure and accurate modeling of hand motion. In this study, we developed a finger exoskeleton with a rolling contact involute joint. Specific implementation methods were investigated, including an analysis of the mechanical characteristics of the involute joint model, the formula derivation of the joint parameter optimization algorithm, and the design process for a finger exoskeleton with an involute joint. Experiments were conducted using a finger exoskeleton prototype to evaluate the output trajectory and grasping force of the finger exoskeleton. An EMG-controlled hand exoskeleton was developed to verify the wearability and functionality of the glove. The experimental results show that the proposed involute joint can provide sufficient fingertip force (10N) while forming a lightweight exoskeleton to assist users with functional hand rehabilitation and grasping activities.
      Citation: Machines
      PubDate: 2022-04-24
      DOI: 10.3390/machines10050301
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 302: Study on the Static Characteristics of a
           Pre-Pressure Single-Action Membrane-Type Restrictor Used in a Single Oil
           Pad

    • Authors: Feng Lu, Zhenzhong Wang, Pengli Lei, Yi Chen
      First page: 302
      Abstract: In order to further improve the static stiffness of the hydrostatic bearing with the membrane-type restrictor, in this study, a static characteristics model of the pre-pressure single-action membrane-type restrictor (PSMR) is derived, and the criteria for achieving the optimum stiffness of the restrictor are summarized. A PSMR design method following the criteria of optimal stiffness is proposed. Then, the effect of design parameters on the performance of the restrictor is accurately evaluated by numerical simulation and orthogonal experiment with the grinder oil pad, as an example. Finally, the performance of the PSMR is compared with that of the traditional restrictors, and the main source of design error of the membrane-type restrictor is discussed. The results show that the effect of the design error of the membrane structure on the performance of the restrictor is reduced to some extent by the parallel oil circuit of the PSMR. In addition, the membrane-type restrictor designed according to the method of this paper theoretically has better static stiffness than the single-action membrane-type restrictor without pre-pressure, with an average improvement of about 14.14%.
      Citation: Machines
      PubDate: 2022-04-24
      DOI: 10.3390/machines10050302
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 303: A Comparative Study on Multi-Criteria
           Decision-Making in Dressing Process for Internal Grinding

    • Authors: Huu-Quang Nguyen, Xuan-Hung Le, Thanh-Tu Nguyen, Quoc-Hoang Tran, Ngoc-Pi Vu
      First page: 303
      Abstract: The MCDM problem is very important and often encountered in life and in engineering as it is used to determine the best solution among various possible alternatives. In this paper, the results of the MCDM problem in the dressing process for internal grinding are presented. To perform this work, an experiment with six input parameters, including the depth and the time of fine dressing, the depth and the time of coarse dressing, non-feeding dressing, and dressing feed rate, was conducted. The experiment was designed according to the Taguchi method with the use of L16 orthogonal arrays. In addition, TOPSIS, MARCOS, EAMR and MAIRCA methods were selected for the MCDM to obtain the minimum SR and the maximum MRR simultaneously. In addition, the weight determination for criteria was implemented by MEREC and entropy methods. From the results, the best solution to the multi-criteria problem for the dressing process in internal grinding has been proposed.
      Citation: Machines
      PubDate: 2022-04-24
      DOI: 10.3390/machines10050303
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 304: Operational Stability Analysis on the
           Roller-Coating Process for a Roll Coating-Simulation Test Equipment

    • Authors: Hongzhan Lv, Kehang Yang, Jia You, Shuyan Wang
      First page: 304
      Abstract: In the research on key technology of radiation-curing coil steel coating, it is necessary to evaluate the coating stability of radiation-curing coil steel coating materials. In this paper, a roll coating-simulation test equipment is proposed to test coating status. Considering the operational stability of the equipment, dynamic vibration response analysis and stability analysis of the roller-coating process are performed on the equipment. The test results show that the rotor vibration of the designed roll coating-simulation test equipment meets the requirements of rotating machinery, and the coating thickness remains stable under the vibration condition, which satisfies the working condition of the test equipment.
      Citation: Machines
      PubDate: 2022-04-25
      DOI: 10.3390/machines10050304
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 305: Design and Control of a Hydraulic Hexapod
           Robot with a Two-Stage Supply Pressure Hydraulic System

    • Authors: Ziqi Liu, Bo Jin, Junkui Dong, Shuo Zhai, Xuan Tang
      First page: 305
      Abstract: This paper focuses on the system design and control strategies of a hydraulic hexapod robot (HHR) ZJUHEX01 with a two-stage supply pressure hydraulic system (TSS). Firstly, a brief introduction is given, including the mechanical structure, the onboard hydraulic system, and the control system architecture. Secondly, the kinematics model and hydraulic system model are built in preparation for the controller design. Then a sliding mode repetitive controller (SMRC) for the separate meter in and separate meter out (SMISMO) hydraulic system is proposed, as well as the valve configuration, to help HHR get better control performance and smaller tracking errors. Furthermore, a high order sliding mode differentiator (HOSMD) is developed to obtain the joint angular velocity and acceleration. Finally, the ADAMS and MATLAB/Simulink co-simulation model is established to verify the effectiveness of the control strategy. Also, the energy consumption of TSS is compared with that of one-stage supply pressure hydraulic system (OSS) to show a great energy-saving effect of 51.94%.
      Citation: Machines
      PubDate: 2022-04-25
      DOI: 10.3390/machines10050305
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 306: Buffering Performance Analysis of an
           Ostrich-like Leg Based on a Seven-Link Parallel Mechanism

    • Authors: Daming Nie, Ruilong Du, Jiangren Tian, Pu Zhang, Fangyan Shen, Jason Gu, Yili Fu
      First page: 306
      Abstract: As one of the fastest running animals on land, the ostrich’s excellent athletic ability benefits from its unique leg structure. Based on the idea of bionics, this paper intends to obtain a kind of robotic leg structure with a similar buffering capacity to that of the ostrich. For this purpose, the structural characteristics of a seven-link parallel mechanism are analyzed firstly, having some specific features similar to ostrich legs, such as the center of mass (COM) located at the root of the leg, a large folding/unfolding ratio, and so on. Then, the kinematic model of the bionic leg is established, and the energy storage of the flexible parts of the leg is investigated. Finally, an impact experiment of the structure onto the ground is carried out to verify the accuracy of the established kinematic model. This paper systematically reveals the nonlinear law of the elasticity of an ostrich-like leg and provides the buffering performance characteristics of the leg in the process of hitting the ground, based on its elastic properties by the kinematic model and the experiment.
      Citation: Machines
      PubDate: 2022-04-25
      DOI: 10.3390/machines10050306
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 307: Experimental Study on the Response of
           Hand-Transmitted Vibration from an EVA Power Tool

    • Authors: Hao Fu, Minghe Jin, Yang Yu, Yang Chen, Peng Zheng
      First page: 307
      Abstract: The objective of this paper is to accurately measure the vibration response of tools and hands by simulating the hand-held power tools, which are operated by astronauts wearing extravehicular spacesuit gloves under microgravity conditions. The total vibration value and the daily vibration exposure of the subject’s hand are obtained. The results show that the opisthenar is more sensitive to the vibration frequency less than 200 Hz. After frequency weighting, the vibration exposure in the composite state of wearing an unpressurized spacesuit glove on the opisthenar is 23.6% greater than the vibration exposure of the palm, and for the bare hand, the percentage is 25.1% under the same condition. Because the operation time of tightening a screw is longer than that of loosening, the tightening operation performed by wearing spacesuit gloves produces 15.7% more mean vibration exposure on the palm and opisthenar than the loosening operation. The results of vibration transmissibility characterized by the total vibration weighted method and the total vibration unweighted method are 0.039 and 0.094, respectively. In comparison with bare hands, the mean daily vibration exposure on the palm and opisthenar in the composite state by wearing spacesuit gloves is 16.3% less, indicating that the unpressurized spacesuit gloves have an effect on vibration reduction. The research reveals the law of hand-transmitted vibration caused by the coupling of the extravehicular activities (EVA) power tools and spacesuit gloves, and provides a novel method for further similar tests and verification of hand-held EVA power tools.
      Citation: Machines
      PubDate: 2022-04-26
      DOI: 10.3390/machines10050307
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 308: Analysis of the Static Performance of a
           Cableless Aerostatic Guideway

    • Authors: Yue Zhou, Zhenjiang Hu, Tao Sun, Xuesen Zhao, Junjie Zhang, Wenjun Zong
      First page: 308
      Abstract: To develop an innovative aerostatic guideway without cable drag force that can be widely applied to ultra-precision machining and measurement technology, it is necessary to analyze the static performance of the aerostatic guideway. The structural properties of the cableless aerostatic guideway, i.e., the bearing capacity and internal pressure distribution, directly affect the accuracy of processing and measurement. In this work, the relevant flow equations of the cableless aerostatic guideway are established by considering the unbalanced micro-scale air film. Moreover, the finite difference method is used to solve the calculation of the global analysis of air film at different positions. In addition, this work compares and analyzes the pressure and fluid velocity vector distributions in balanced and unbalanced states and investigates the effect of varying the thicknesses of the air film on static characteristics such as bearing capacity and stiffness. By comparing the balanced and unbalanced states under the same conditions, the obtained results show that in the unbalanced situation, the bearing capacity is lower by 11.69 percent and the stiffness is slightly higher (by 16.67 percent). Furthermore, the related experiments verify the predicted dependence of the bearing capacity on the thickness of the air film, and further demonstrate the feasibility of the proposed structure of the cableless aerostatic guideway. This work provides a technical reference for the design of a cableless aerostatic guideway.
      Citation: Machines
      PubDate: 2022-04-26
      DOI: 10.3390/machines10050308
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 309: Design of Electromagnetic Control of the
           Needle Gripping Mechanism

    • Authors: Jiří Komárek, Vojtěch Klogner
      First page: 309
      Abstract: This paper deals with the modification of the mechanical system of the needle bar. The purpose of this work is to reduce the vibration and noise of the sewing machine for creating a decorative stitch. A special floating needle is used to sew this stitch, in which two mechanical systems of needle bars handover through the sewn material, so that a perfect imitation of a hand stitch is created. The original system, which controls the release of the needle at the handover location by abruptly stopping the needle bar control element, could be replaced by a new system that uses magnetic force to release the needle. In addition to the usual design procedure, numerical simulations of the attractive force of the electromagnet are also used in the design of a suitable electromagnet. At the same time, an electrical circuit is also designed to allow the needle to be released and gripped quickly. The advantages of the new system lie not only in reducing vibrations and the associated increase in the operation speed of the machine, but also in making it easier for the machine to switch to possible automated or semi-automated production.
      Citation: Machines
      PubDate: 2022-04-26
      DOI: 10.3390/machines10050309
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 310: USV Application Scenario Expansion Based on
           Motion Control, Path Following and Velocity Planning

    • Authors: Ziang Feng, Zaisheng Pan, Wei Chen, Yong Liu, Jianxing Leng
      First page: 310
      Abstract: The ability of unmanned surface vehicles (USV) on motion control and the accurate following of preset paths is the embodiment of its autonomy and intelligence, while there is extensive room for improvement when expanding its application scenarios. In this paper, a model fusion of USV and preset path was carried out through the Serret-Frenet coordinate system. Control strategies were then scrupulously designed with the help of Lyapunov stability theory, including resultant velocity control in the presence of drift angle, course control based on the nonlinear backstepping method, and reference point velocity control as a virtual control variable. Specifically, based on USV resultant velocity control, this paper proposes respective solutions for two common scenarios through velocity planning. In a derailment correction scenario, an adaptive reference velocity was designed according to the position and attitude of USV, which promoted its maneuverability remarkably. In a dynamic obstacle avoidance scenario, an appropriate velocity curve was searched by dynamic programming on ST graph and optimized by quadratic programming, which enabled USV to evade obstacles without changing the original path. Simulation results proved the convergence and reliability of the motion control strategies and path following algorithm. Furthermore, velocity planning was verified to perform effectively in both scenarios.
      Citation: Machines
      PubDate: 2022-04-26
      DOI: 10.3390/machines10050310
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 311: Equivalent Identification of Distributed
           Random Dynamic Load by Using K–L Decomposition and Sparse
           Representation

    • Authors: Kun Li, Yue Zhao, Zhuo Fu, Chenghao Tan, Xianfeng Man, Chi Liu
      First page: 311
      Abstract: By aiming at the common distributed random dynamic loads in engineering practice, an equivalent identification method that is based on K–L decomposition and sparse representation is proposed. Considering that the establishment of a probability model of the distributed random dynamic load is usually unfeasible because of the requirement of a large number of samples, this method describes it by using an interval process model. Through K–L series expansion, the interval process model of the distributed random dynamic load is recast as the sum of the load median function and the load uncertainty. Then, the original load identification problem is transformed into two deterministic ones: the identification of the load median function and the reconstruction of the load covariance matrix, which reveals the load uncertainty characteristics. By integrating the structural modal parameters, and by adopting the Green’s kernel function method and sparse representation, the continuously distributed load median function is equivalently identified as several concentrated dynamic loads that act on the appropriate positions. On the basis of the realization of the first inverse problem, the forward model of the load covariance matrix reconstruction is derived by using K–L series expansion and spectral decomposition. The resolutions to both inverse problems are assisted by the regularization operation so as to overcome the inherent ill-posedness. At the end, a numerical example is presented to show the effectiveness of the proposed method.
      Citation: Machines
      PubDate: 2022-04-26
      DOI: 10.3390/machines10050311
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 312: An Unscented Kalman Filter Online
           Identification Approach for a Nonlinear Ship Motion Model Using a
           Self-Navigation Test

    • Authors: Jian Zheng, Duowen Yan, Ming Yan, Yun Li, Yabing Zhao
      First page: 312
      Abstract: This paper proposes a method for the online parameter identification of nonlinear ship motion systems. First, the motion system of a ship is nonlinear, and in the course of sailing, the motion parameters of the ship will change with the change of the motion state of the ship and the sailing environment. To achieve the effect of real-time identification, we adopted an online receding horizon identification method. Second, identification parameters are the essential elements in the navigation control of intelligent merchant ships, and high-precision identification results can achieve better control effects. Therefore, we used an unscented Kalman filter (UKF) that has simpler mathematical structure and higher feedback efficiency than other identification algorithms listed in this paper, such as extended the Kalman filter, Kalman filtering and Ordinary Least Squares, as the identification scheme design algorithm, which is applied to ship motion system identification. Then, to solve the problem of significant identification errors in complex environments, we design a navigation identification framework combining a UKF and rolling wavelet denoising to realize the effect of the online identification of ships. Finally, a Korea Research Institute of Ships and Ocean Engineering (KRISO) Container Ship (KCS) was used for a self-navigation model experiment and data collection. The collected data and identification data were compared and analyzed. By comparing different identification algorithms before and after denoising, it was verified that the UKF algorithm proposed in this paper is superior relative to other traditional algorithms in identifying ship motion systems.
      Citation: Machines
      PubDate: 2022-04-26
      DOI: 10.3390/machines10050312
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 313: A Fault Diagnosis Model for Coaxial-Rotor
           Unit Using Bidirectional Gate Recurrent Unit and Highway Network

    • Authors: Zhaoqin Peng, Kunyu Dong, Yan Wang, Xucong Huang
      First page: 313
      Abstract: A turbojet engine is the most significant part of an Internal Combustion Engine (ICE) for Hybrid Electric Vehicles. Specifically, the coaxial-rotor unit is the key component, whose performance largely affects the working efficiency. Thereby, the fault diagnosis methods for coaxial-rotor units is a main focus. In line with our test results, the bearing circlip is the most vulnerable element while rotating. Moreover, the low-speed rotating fault diagnosis is even challenging for current methods. Since the fault diagnosis on the bearing circlip of coaxial-rotor units is absent, this paper establishes a test rig on a running coaxial-rotor unit under different working conditions. The three-directional vibration signals are collected and analyzed to demonstrate the working states. On the task of bearing circlip failure classification, a deep-learning-based model using the Bidirectional Gate Recurrent Unit and the Highway Network is developed, which is capable of capturing hidden features and removing unrelated information. For working performance evaluation, experiments on the data of different rotating speeds are carried out. Among all the fault diagnosis methods, our model is the best approach and achieves an average accuracy of 99.4%. The encouraging results reveal that the proposed model is effective in both the high-speed and low-speed fault diagnosis of bearing circlip malfunction.
      Citation: Machines
      PubDate: 2022-04-27
      DOI: 10.3390/machines10050313
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 314: A Novel Design of an Inner Rotor for
           Optimizing the Air-Gap Magnetic Field of Hollow-Cup Motors

    • Authors: Jinji Sun, Jianyi Ren, Haoxi Sun
      First page: 314
      Abstract: In order to obtain a high power density, spacecraft usually use hollow-cup motors with trapezoidal air-gap magnetic field waveforms. However, due to structural issues, the hollow-cup motor has the problem that the waveform of the air-gap magnetic field is inconsistent with the ideal trapezoidal waveform, which causes torque ripples. In order to reduce torque ripples, the existing method only changes the structure of PMs; the changed PMs are difficult to magnetize and manufacture, which causes the air-gap magnetic field waveform to be unsuitable as the ideal waveform. This paper proposes a novel design of an inner rotor of a hollow-cup motor with an eccentric inner rotor based on the characteristics that the hollow-cup motor has inner and outer rotors and the two rotors rotate synchronously during operation. First, the influencing factors of the air-gap magnetic field are analyzed and the mathematical model of the eccentric inner rotor is established. Then, an eccentric model is established by finite element analysis, which proves that the eccentricity of the inner rotor can make the air-gap magnetic field waveform closer to the ideal trapezoid. Finally, a prototype based on the optimal eccentricity value is developed, verifying the effectiveness of the novel design of the inner rotor.
      Citation: Machines
      PubDate: 2022-04-27
      DOI: 10.3390/machines10050314
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 315: Investigation of Cell Concentration Change
           and Cell Aggregation Due to Cell Sedimentation during Inkjet-Based
           Bioprinting of Cell-Laden Bioink

    • Authors: Heqi Xu, Dulce Maria Martinez Salazar, Changxue Xu
      First page: 315
      Abstract: Recently, even though 3D bioprinting has made it possible to fabricate 3D artificial tissues/organs, it still faces several significant challenges such as cell sedimentation and aggregation. As the essential element of 3D bioprinting, bioink is usually composed of biological materials and living cells. Guided by the initially dominant gravitational force, cells sediment, resulting in the non-uniformity of the bioink and the decrease in the printing reliability. This study primarily focuses on the quantification of cell sedimentation-induced cell concentration change and cell aggregation within the bioink reservoir during inkjet-based bioprinting. The major conclusions are summarized as follows: (1) with 0.5% (w/v) sodium alginate, after around 40-min printing time, almost all the cells have sedimented from the top region. The cell concentration at the bottom is measured to be more than doubled after 60-min printing time. On the contrary, due to the slow cell sedimentation velocity with 1.5% and 3% (w/v) sodium alginate, the uniformity of the bioink is still highly maintained after 60-min printing; and (2) more cell aggregates are observed at the bottom with the printing time, and severe cell aggregation phenomenon has been observed at the bottom using 0.5% (w/v) sodium alginate starting from 40-min printing time. With the highest cell concentration 2 × 106 cells/mL, 60.9% of the cells have formed cell aggregates at 40-min printing time. However, cell aggregation is dramatically suppressed by increasing the polymer concentration.
      Citation: Machines
      PubDate: 2022-04-28
      DOI: 10.3390/machines10050315
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 316: Defining the Number of Mobile Robotic
           Systems Needed for Reconfiguration of Modular Manufacturing Systems via
           Simulation

    • Authors: Martin Marschall, Milan Gregor, Lukáš Ďurica, Vladimír Vavrík, Tomáš Bielik, Patrik Grznár, Štefan Mozol
      First page: 316
      Abstract: The European vision of the Factory of the Future is based on increasing competition and sustainability by transformation from cost orientation to high-adding value with technical and organisational innovations. One of the expected outcomes is an increase in modularisation, i.e., the reconfigurability of the technical system in manufacturing conditions. Modular manufacturing systems (MMS), will consist of modular platforms (MP) that are capable of rapid rebuilding, and reconfiguration performed by adding or removing a module by Mobile Robotic Systems (MRS). In the conditions of MMS, to make the most efficient use of reconfiguration MRS capacities, it is necessary to know the optimal ratio of these MRS to the number of modular platforms (MP) used in MMS, which does not exist today. This ratio will help industrial companies that are deploying MMS-based solutions to plan the number of MRSs needed to reconfigure deployed systems. As a method of determining this optimal ratio, an experimental approach via simulation was chosen, using data from custom MRS and MP prototypes with testing different layouts of modular platforms with the view of warehouse layout, manufacturing island, manufacturing island power supply, and MRS. Based on the results, it can be determined that the MP-MRS limit ratio is 2:1, where the further increase in MRS has only a minimal impact on the reconfiguration period. With the reduction of MP transferred to one MRS, there is a gradual decrease in the time required for reconfiguration. When the ratio of 1:1 is attained, the time required for reconfiguration lowers, but not as dramatically as in bigger ratios.
      Citation: Machines
      PubDate: 2022-04-28
      DOI: 10.3390/machines10050316
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 317: Review on Motion and Load-Bearing
           Characteristics of the Planetary Roller Screw Mechanism

    • Authors: Xin Li, Geng Liu, Xiaojun Fu, Shangjun Ma
      First page: 317
      Abstract: Studying the motion and load-bearing characteristics of the planetary roller screw mechanism is the basis for the structural design and performance optimisation of the mechanism. The mechanical structures and working principles of different kinds of planetary roller screw mechanisms are summarised. Published papers on kinematic, load-bearing and dynamic models of the planetary roller screw mechanism are reviewed. Based on the slip state in point contacts at the screw–roller and the nut–roller interfaces, the kinematic models are divided into three types. The finite element method and numerical theory are the two main methods used to develop the load-bearing models. Current dynamic models differ mainly concerning whether they take the rotation of the screw into consideration. In this work, each kind of model is presented in detail along with relevant literature. The main conclusions for each type of model are discussed, and an overview of the future evolution of motion and load-bearing characteristics of the planetary roller screw mechanism are given.
      Citation: Machines
      PubDate: 2022-04-28
      DOI: 10.3390/machines10050317
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 318: Active Assistive Design and Multiaxis
           Self-Tuning Control of a Novel Lower Limb Rehabilitation Exoskeleton

    • Authors: Cheng-Tang Pan, Ming-Chan Lee, Jhih-Syuan Huang, Chun-Chieh Chang, Zheng-Yu Hoe, Kuan-Ming Li
      First page: 318
      Abstract: This paper presented the mechanical design and control of a lower limb rehabilitation exoskeleton named “the second lower limb rehabilitation exoskeleton (LLRE-II)”. The exoskeleton with a lightweight mechanism comprises a 16-cm stepless adjustable thigh and calf rod. The LLRE-II weighs less than 16 kg and has four degrees of freedom on each leg, including the waist, hip, knee, and ankle, which ensures fitted wear and comfort. Motors and harmonic drives were installed on the joints of the hip and knee to operate the exoskeleton. Meanwhile, master and slave motor controllers were programmed using a Texas Instruments microcontroller (TMS320F28069) for the walking gait commands and evaluation boards (TMS320F28069/DRV8301) of the joints. A self-tuning multiaxis control system was developed, and the performance of the controller was investigated through experiments. The experimental results showed that the mechanical design and control system exhibit adequate performance. Trajectory tracking errors were eliminated, and the root mean square errors reduced from 6.45 to 1.22 and from 4.15 to 3.09 for the hip and knee, respectively.
      Citation: Machines
      PubDate: 2022-04-28
      DOI: 10.3390/machines10050318
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 319: Feature-Based and Process-Based
           Manufacturing Cost Estimation

    • Authors: Fangwei Ning, Hongquan Qu, Yan Shi, Maolin Cai, Weiqing Xu
      First page: 319
      Abstract: The demand for mass custom parts is increasing, estimating the cost of parts to a high degree of efficiency is a matter of great concern to most manufacturing companies. Under the premise of machining operations, cost estimation based on features and processes yields high estimation accuracy, but it necessitates accurately identifying a part’s machining features and establishing the relationship between the feature and the cost. Accordingly, a feature recognition method based on syntactic pattern recognition is proposed herein. The proposed method provides a more precise feature definition and easily describes complex features using constraints. To establish the relationships between geometric features, processing modes, and cost, this study proposes a method of describing the features and the processing mode using feature quantities and adopts deep learning technology to establish the relationship between feature quantities and cost. By comparing a back propagation (BP) network and a convolutional neural network (CNN) it can be concluded that a CNN using the “RMSProp” optimizer exhibits higher accuracy.
      Citation: Machines
      PubDate: 2022-04-28
      DOI: 10.3390/machines10050319
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 320: Fuzzy Sliding Mode Control for Microbial
           Fuel Cells

    • Authors: Tianyu Ouyang, Fengying Ma, Baolong Zhu, Peng Ji, Lei Lian
      First page: 320
      Abstract: The microbial fuel cells (MFCs) are a kind of green energy with good prospects, which provides an effective solution to the problem of unsustainable development of energy today. Aiming at the problem that MFCs are susceptible to various external disturbances, a sliding mode (SM) controller for MFCs is designed in this paper. The controller can effectively reduce the influence of external disturbance on voltage output and improve the practicability of microbial fuel cells (MFC). At the same time, aiming at the chattering problem of the basic SM control, a fuzzy sliding mode (FSM) control method is proposed by combining the fuzzy logic theory and the SM control. The design method of FSM controller is given by using Lyapunov theory. The method can adaptively adjust the parameters according to the difference between the actual value of the substrate concentration and the set value. The controller can reduce the system input chattering and the influence of external disturbances on the system output. Simulation results show that compared with SM control and backstepping control, the designed method has smaller steady-state error and overshoot.
      Citation: Machines
      PubDate: 2022-04-28
      DOI: 10.3390/machines10050320
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 321: Kinematic Modeling and Motion Planning of
           the Mobile Manipulator Agri.Q for Precision Agriculture

    • Authors: Giovanni Colucci, Andrea Botta, Luigi Tagliavini, Paride Cavallone, Lorenzo Baglieri, Giuseppe Quaglia
      First page: 321
      Abstract: In recent years, the study of robotic systems for agriculture, a modern research field often shortened as “precision agriculture”, has become highly relevant, especially for those repetitive actions that can be automated thanks to innovative robotic solutions. This paper presents the kinematic model and a motion planning pipeline for a mobile manipulator specifically designed for precision agriculture applications, such as crop sampling and monitoring, formed by a novel articulated mobile base and a commercial collaborative manipulator with seven degrees of freedom. Starting from the models of the two subsystems, characterized by an adjustable position and orientation of the manipulator with respect to the mobile base, the linear mapping that describes the differential kinematics of the whole custom system is expressed as a function of the input commands. To perform pick–and–place tasks, a motion planning algorithm, based on the manipulator manipulability index mapping and a closed form inverse kinematics solution is presented. The motion of the system is based on the decoupling of the base and the arm mobility, and the paper discusses how the base can be properly used for manipulator positioning purposes. The closed form inverse kinematics solution is also provided as an open-source Matlab code.
      Citation: Machines
      PubDate: 2022-04-29
      DOI: 10.3390/machines10050321
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 322: Failure Analysis of a Cylindrical Roller
           Bearing Caused by Excessive Tightening Axial Force

    • Authors: Xueqin Hou, Qing Diao, Yujian Liu, Changkui Liu, Zheng Zhang, Chunhu Tao
      First page: 322
      Abstract: The premature failure of a cylindrical roller bearing took place during service, with a total operation time of 100 h. The failure cause was analyzed by macroscopic and microscopic observation, metallographic analysis, hardness testing, tightening axial force influence analysis, and test verification. The results show that failure modes of the bearing are contact fatigue spalling, wear, and fatigue fracture. The outer ring, inner ring, rollers, and cages all have suffered relatively heavy damage in the sides corresponding to the bearing side with laser marking. Excessive load, induced by the excessive tightening axial force, derived from the lock nut, is the cause of the bearing failure. The failure mechanism is that excessive tightening axial force caused a great deformation and cylindricity increase of the inner ring raceway, which induced high local contact stress between one side of the ring raceways, as well as the corresponding ends of the rollers, resulting in the bearing failure. At last, measures for prevention of this failure are put forward as follows: controlling the tightening axial force within the range of technical requirement, increasing the convexity of the inner ring raceway and rollers, and decreasing the grinding undercut size of the inner ring.
      Citation: Machines
      PubDate: 2022-04-29
      DOI: 10.3390/machines10050322
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 323: A Conflict Solving Process Based on Mapping
           between Physical Parameters and Engineering Parameters

    • Authors: Peng Zhang, Qianhao Ma, Zifeng Nie, Xindi Li
      First page: 323
      Abstract: With the continuous expansion of system scale, the parameter coupling of the system is prominent. Due to limitations in knowledge and experience, it is difficult for designers to objectively analyze the interaction relationship between parameters, resulting in the low accuracy of engineering parameter selection, hence affecting conflict solving. In order to improve the accuracy of engineering parameter selection and the efficiency of conflict solving, this paper proposes a conflict solving process based on mapping between physical parameters and engineering parameters. First, the physical parameters related to the components of the system function model are extracted, and dimensional analysis is used to construct a physical parameter logical network. Secondly, the physical parameter change path related to the problem in the physical parameter logical network is found, and the physical parameter sets corresponding to both conflicting parties are obtained. Then, the engineering parameters corresponding to conflicts can be selected through the mapping model between physical parameters and engineering parameters, which is trained by a neural network with the sample data of physical parameter sets and engineering parameters in existing cases. Finally, Theory of Inventive Problem Solving (TRIZ) tools are used to solve conflicts, and the final design scheme is obtained through evaluation. The feasibility and effectiveness of the proposed method are verified by redesigning a bulk traditional Chinese medicine dispenser.
      Citation: Machines
      PubDate: 2022-04-29
      DOI: 10.3390/machines10050323
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 324: Dual-Modal Hybrid Control for an Upper-Limb
           Rehabilitation Robot

    • Authors: Guang Feng, Jiaji Zhang, Guokun Zuo, Maoqin Li, Dexin Jiang, Lei Yang
      First page: 324
      Abstract: The recovery treatment of motor dysfunction plays a crucial role in rehabilitation therapy. Rehabilitation robots are partially or fully replacing therapists in assisting patients in exercise by advantage of robot technologies. However, the rehabilitation training system is not yet intelligent enough to provide suitable exercise modes based on the exercise intentions of patients with different motor abilities. In this paper, a dual-modal hybrid self-switching control strategy (DHSS) is proposed to automatically determine the exercise mode of patients, i.e., passive and assistive exercise mode. In this strategy, the potential field method and the ADRC position control are employed to plan trajectories and assist patients’ training. Dual-modal self-switching rules based on the motor and impulse information of patients are presented to identify patients’ motor abilities. Finally, the DHSS assisted five subjects in performing the training with an average deviation error of less than 2 mm in both exercise modes. The experimental results demonstrate that the muscle activation of the subjects differed significantly in different modes. It also verifies that DHSS is reasonable and effective, which helps patients to train independently without therapists.
      Citation: Machines
      PubDate: 2022-04-29
      DOI: 10.3390/machines10050324
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 325: New Design of Hy-Vo Chain Based on the
           Ultra-Small Rolling Radius

    • Authors: Lichi An, Yabing Cheng, Jiabao Li, Weilong Xu
      First page: 325
      Abstract: To improve the system meshing performance and the chain stability, a totally new type Hy-Vo chain with an ultra-small rolling radius is proposed in this research. According to the rolling theory of the rocker pin, the design method and the meshing system for the new Hy-Vo chain are proposed. Based on the analysis model of polygonal action, by calculating a specific example, it is proved that the variable pitch characteristic of the new Hy-Vo chain is controllable. Through comparing the system center distance fluctuations for the new and the classical Hy-Vo chain, it is shown that both the system fluctuation difference and the system running deviation are all smaller for the new Hy-Vo chain. Combined with the analysis of Multi Flexible Body Dynamics (MFBD), for the new Hy-Vo chain plate and the rocker pin, the stress distribution is more uniform, and the chain life is longer. As a result, the new Hy-Vo chain with the ultra-small rolling radius has a better meshing performance and fatigue resistance, as well as better process economy. Moreover, the new design proposed in this paper is not only a novel structure for the Hy-Vo chain drive, but it also reveals the meshing mechanism and the controllable variable pitch characteristic.
      Citation: Machines
      PubDate: 2022-04-29
      DOI: 10.3390/machines10050325
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 326: Multi-Domain Weighted Transfer Adversarial
           Network for the Cross-Domain Intelligent Fault Diagnosis of Bearings

    • Authors: Yuanfei Wang, Shihao Li, Feng Jia, Jianjun Shen
      First page: 326
      Abstract: Transfer learning is a topic that has attracted attention for the intelligent fault diagnosis of bearings since it addresses bearing datasets that have different distributions. However, the traditional intelligent fault diagnosis methods based on transfer learning have the following two shortcomings. (1) The multi-mode structure characteristics of bearing datasets are neglected. (2) Some local regions of the bearing signals may not be suitable for transfer due to signal fluctuation. Therefore, a multi-domain weighted adversarial transfer network is proposed for the cross-domain intelligent fault diagnosis of bearings. In the proposed method, multi-domain adversarial and attention weighting modules are designed to consider bearing multi-mode structure characteristics and solve the influence of local non-transferability regions of signals, respectively. Two diagnosis cases are used to verify the proposed method. The results show that the proposed method is able to extract domain invariant features for different cross-domain diagnosis cases, and thus improves the accuracy of fault identification.
      Citation: Machines
      PubDate: 2022-04-29
      DOI: 10.3390/machines10050326
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 327: Research of U-Net-Based CNN Architectures
           for Metal Surface Defect Detection

    • Authors: Ihor Konovalenko, Pavlo Maruschak, Janette Brezinová, Olegas Prentkovskis, Jakub Brezina
      First page: 327
      Abstract: The quality, wear and safety of metal structures can be controlled effectively, provided that surface defects, which occur on metal structures, are detected at the right time. Over the past 10 years, researchers have proposed a number of neural network architectures that have shown high efficiency in various areas, including image classification, segmentation and recognition. However, choosing the best architecture for this particular task is often problematic. In order to compare various techniques for detecting defects such as “scratch abrasion”, we created and investigated U-Net-like architectures with encoders such as ResNet, SEResNet, SEResNeXt, DenseNet, InceptionV3, Inception-ResNetV2, MobileNet and EfficientNet. The relationship between training validation metrics and final segmentation test metrics was investigated. The correlation between the loss function, the , , , and validation metrics and test metrics was calculated. Recognition accuracy was analyzed as affected by the optimizer during neural network training. In the context of this problem, neural networks trained using the stochastic gradient descent optimizer with Nesterov momentum were found to have the best generalizing properties. To select the best model during its training on the basis of the validation metrics, the main test metrics of recognition quality (Dice similarity coefficient) were analyzed depending on the validation metrics. The ResNet and DenseNet models were found to achieve the best generalizing properties for our task. The highest recognition accuracy was attained using the U-Net model with a ResNet152 backbone. The results obtained on the test dataset were and .
      Citation: Machines
      PubDate: 2022-04-29
      DOI: 10.3390/machines10050327
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 328: Mitigation of High-Frequency Eddy Current
           Losses in Hairpin Winding Machines

    • Authors: Ahmed Selema, Mohamed N. Ibrahim, Peter Sergeant
      First page: 328
      Abstract: In high-speed and high-frequency electric machines, one of the major issues that impacts the performance and capability of a machine is the high-frequency eddy current losses in the windings. This work deals with AC winding losses in flat rectangular conductors. Aiming for eddy current loss mitigation, two different materials are investigated and compared for the same winding design, namely copper and aluminum. Using the finite element method (FEM), the conductor loss and current density behavior are simulated at the strand level. Further, in order to verify the simulated losses, the AC losses are measured and compared over a wide range of frequencies. Finally, recommendations are provided based on the obtained measurements to identify the best winding topology that is most suitable for automotive applications.
      Citation: Machines
      PubDate: 2022-04-30
      DOI: 10.3390/machines10050328
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 329: Optimal Synthesis of Loader Drive
           Mechanisms: A Group Robust Decision-Making Rule Generation Approach

    • Authors: Goran Petrović, Jovan Pavlović, Miloš Madić, Dragan Marinković
      First page: 329
      Abstract: The objective of this paper is to present a novel, hybrid group multi-criteria decision approach that can be used to evaluate alternatives for the optimal synthesis of loader drive mechanisms. In most product design engineering groups, experts have expertise in different areas and robust decision-making is necessary to integrate a number of opposing opinions, attitudes, and solutions. This study presents the application of an integrated approach for decision-making, i.e., the generation of a robust decision-making rule for group decision-making (RDMR-G) by combining different multi-criteria decision-making (MCDM) methods and Taguchi’s robust quality engineering principles. The basic idea behind this article was to create an approach that enables the comprehensive and robust consideration of expert opinions given the existence of numerous objective and subjective methods for determining the criteria weights, which are crucial to the final ranking of alternatives in any decision-making problem. In order to set the optimal configuration of a loader drive mechanism, five experts, all with a high level of experience and knowledge in this field, considered twenty-six different kinematic chain construction solutions, i.e., alternatives, and evaluated them with respect to six criteria. The obtained results and rankings provided by each expert and each criteria weighting method were compared using Kendall’s τb and Spearman’s ρ tests. As an example, this paper demonstrates the practical application of a RDMR-G approach and in doing so contributes to the literature in the fields of product design engineering and decision-making.
      Citation: Machines
      PubDate: 2022-05-01
      DOI: 10.3390/machines10050329
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 330: The Key Role of 3D Printing Technologies in
           the Further Development of Electrical Machines

    • Authors: Loránd Szabó, Dénes Fodor
      First page: 330
      Abstract: There is a strong general demand for the permanent improvement of electrical machines. Nowadays, these are at their near maximum potential, and even small further improvements can only be achieved with great effort and high cost. The single solution should be a paradigm shift in their development, by using radically new approaches to topology, materials, and fabrication. Therefore, the application of diverse 3D printing techniques for advanced fabrication in this field is inevitable. Therefore, these new approaches are receiving a great deal of attention among electrical machines designers. In the paper, the possible applications of these new fabrication technologies in the field of electrical machines are surveyed. The focus is set on emphasizing the advancement over the traditional manufacturing approaches.
      Citation: Machines
      PubDate: 2022-05-01
      DOI: 10.3390/machines10050330
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 331: Modeling and Predicting the Machined Surface
           Roughness and Milling Power in Scot’s Pine Helical Milling Process

    • Authors: Rongrong Li, Fan Yang, Xiaodong Wang
      First page: 331
      Abstract: Helical milling with the advantages of stable machining process, a well-machined surface quality, etc., is an interest of researchers and producers. Machined surface roughness (arithmetic mean deviation (Ra) and maximum height of the assessed profile (Rz)) and milling power consumption as two main machining characteristic parameters were studied and chosen as response factors to evaluate the machinability of Scots pine helical milling. Input variables included helical angle of milling cutter, rotation speed of main shaft, and depth of milling. Response surface methodology was applied for the design of experiments, data processing and analysis, and optimization of the processing parameters. The results showed that Ra and Rz decreased with an increase in helical angle and rotation speed of main shaft, though increased with an increase in depth of milling. Milling power increased when the helical angle and depth of milling increased and showed a slight downward trend as the rotational speed increased. The quadratic models were applied to predict the values of Ra, Rz, and milling power due to the high values of R2 of 0.9895, 0.9905, and 0.9885, respectively. The plot of predicted and actual values also indicated that the created models had good predictability. The optimized combination of helical angle, rotation speed, and depth of milling are 64°, 7500 r/min, and 0.5 mm, respectively. The effects of input variables and the quantitative relation between input variables and response variables were revealed clearly. These achievements will be useful for guiding the selection of helical milling parameters to achieve the purposes of improving processed surface quality and saving the processing power consumption.
      Citation: Machines
      PubDate: 2022-05-01
      DOI: 10.3390/machines10050331
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 332: Obstacle Detection for Autonomous Guided
           Vehicles through Point Cloud Clustering Using Depth Data

    • Authors: Micael Pires, Pedro Couto, António Santos, Vítor Filipe
      First page: 332
      Abstract: Autonomous driving is one of the fastest developing fields of robotics. With the ever-growing interest in autonomous driving, the ability to provide robots with both efficient and safe navigation capabilities is of paramount significance. With the continuous development of automation technology, higher levels of autonomous driving can be achieved with vision-based methodologies. Moreover, materials handling in industrial assembly lines can be performed efficiently using automated guided vehicles (AGVs). However, the visual perception of industrial environments is complex due to the existence of many obstacles in pre-defined routes. With the INDTECH 4.0 project, we aim to develop an autonomous navigation system, allowing the AGV to detect and avoid obstacles based in the processing of depth data acquired with a frontal depth camera mounted on the AGV. Applying the RANSAC (random sample consensus) and Euclidean clustering algorithms to the 3D point clouds captured by the camera, we can isolate obstacles from the ground plane and separate them into clusters. The clusters give information about the location of obstacles with respect to the AGV position. In experiments conducted outdoors and indoors, the results revealed that the method is very effective, returning high percentages of detection for most tests.
      Citation: Machines
      PubDate: 2022-05-02
      DOI: 10.3390/machines10050332
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 333: Feedforward–Feedback Controller Based
           on a Trained Quaternion Neural Network Using a Generalised HRHRHR Calculus
           with Application to Trajectory Control of a Three-Link Robot Manipulator

    • Authors: Kazuhiko Takahashi, Eri Tano, Masafumi Hashimoto
      First page: 333
      Abstract: This study derives a learning algorithm for a quaternion neural network using the steepest descent method extended to quaternion numbers. This applies the generalised Hamiltonian–Real calculus to obtain derivatives of a real–valued cost function concerning quaternion variables and designs a feedback–feedforward controller as a control system application using such a network. The quaternion neural network is trained in real-time by introducing a feedback error learning framework to the controller. Thus, the quaternion neural network-based controller functions as an adaptive-type controller. The designed controller is applied to the control problem of a three-link robot manipulator, with the control task of making the robot manipulator’s end effector follow a desired trajectory in the Cartesian space. Computational experiments are conducted to investigate the learning capability and the characteristics of the quaternion neural network used in the controller. The experimental results confirm the feasibility of using the derived learning algorithm based on the generalised Hamiltonian–Real calculus to train the quaternion neural network and the availability of such a network for a control systems application.
      Citation: Machines
      PubDate: 2022-05-02
      DOI: 10.3390/machines10050333
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 334: Sub-Fiber Scale Precision Dicing of Aramid
           Fiber-Reinforced Plastic Composites

    • Authors: Quan Wen, Jintao Hu, Zewei Yuan
      First page: 334
      Abstract: Aramid fiber-reinforced plastic (AFRP) composites are widely used in aerospace, rail transit, marine and military industries, due to their high specific strength, high impact resistance, fatigue resistance and excellent designable properties. In order to meet different application requirements, cutting processes need to be carried out, such as window opening, edge cutting and slit cutting. However, the characteristics of high tensile strength and toughness, low interlaminar strength, non-uniformity and anisotropy make AFRP composites a difficult-to-machine material. They are prone to produce rough cutting surfaces and cutting damages including burr, wire drawing, delamination, resin burn, material flanging, etc. To solve this problem, the ultra-thin diamond dicing blade was used for high-speed cutting of AFRP composites in sub-fiber scale in this research. The influence of process parameters on cutting force, cutting temperature, maximum spindle current, tool wear and cutting surface quality were investigated by establishing the cutting force model, L16(45) orthogonal experiment, single factor experiment, range analysis and variance analysis. The theoretical and experimental results show that cutting AFRP composites with ultra-thin diamond dicing blade can obtain smooth surfaces without common cutting damages. When the cutting speed is 91.11 m/s (spindle speed n = 30,000 r/min), the cutting depth is 0.2 mm and the feed speed is 5 mm/s, the surface roughness Ra can be as low as 32 nm, which realize the precision cutting of AFRP composites.
      Citation: Machines
      PubDate: 2022-05-03
      DOI: 10.3390/machines10050334
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 335: Operator & Fractional Order Based
           Nonlinear Robust Control for a Spiral Counter-Flow Heat Exchanger with
           Uncertainties and Disturbances

    • Authors: Guanqiang Dong, Mingcong Deng
      First page: 335
      Abstract: This paper studies operator and fractional order nonlinear robust control for a spiral counter-flow heat exchanger with uncertainties and disturbances. First, preliminary concepts are presented concerning fractional order derivative and calculus, fractional order operator theory. Then, the problem statement about nonlinear fractional order derivative equation with uncertainties is described. Third, the design of an operator fractional order controller and fractional order PID controller and determination of several related parameters is described. Simulations were performed to verify tracking and anti-disturbance performance by comparison to different control cases; verification is described and concluding remarks provided.
      Citation: Machines
      PubDate: 2022-05-04
      DOI: 10.3390/machines10050335
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 336: Two-Stage Multi-Scale Fault Diagnosis Method
           for Rolling Bearings with Imbalanced Data

    • Authors: Minglei Zheng, Qi Chang, Junfeng Man, Yi Liu, Yiping Shen
      First page: 336
      Abstract: Intelligent bearing fault diagnosis is a necessary approach to ensure the stable operation of rotating machinery. However, it is usually difficult to collect fault data under actual working conditions, leading to a serious imbalance in training datasets, thus reducing the effectiveness of data-driven diagnostic methods. During the stage of data augmentation, a multi-scale progressive generative adversarial network (MS-PGAN) is used to learn the distribution mapping relationship from normal samples to fault samples with transfer learning, which stably generates fault samples at different scales for dataset augmentation through progressive adversarial training. During the stage of fault diagnosis, the MACNN-BiLSTM method is proposed, based on a multi-scale attention fusion mechanism that can adaptively fuse the local frequency features and global timing features extracted from the input signals of multiple scales to achieve fault diagnosis. Using the UConn and CWRU datasets, the proposed method achieves higher fault diagnosis accuracy than is achieved by several comparative methods on data augmentation and fault diagnosis. Experimental results demonstrate that the proposed method can stably generate high-quality spectrum signals and extract multi-scale features, with better classification accuracy, robustness, and generalization.
      Citation: Machines
      PubDate: 2022-05-04
      DOI: 10.3390/machines10050336
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 337: Reliability Assessment Method Based on
           Condition Information by Using Improved Proportional Covariate Model

    • Authors: Baojia Chen, Zhengkun Chen, Fafa Chen, Wenrong Xiao, Nengqi Xiao, Wenlong Fu, Gongfa Li
      First page: 337
      Abstract: If sufficient historical failure life data exist, the failure distribution of the system can be estimated to identify the system initial hazard function. The conventional proportional covariate model (PCM) can reveal the dynamic relationship between the response covariates and the system hazard rate. The system hazard rate function can be constantly updated by the response covariates through the basic covariate function (BCF). Under the circumstances of sparse or zero failure data, the key point of the PCM reliability assessment method is to determine the proportional factor between covariates and the hazard rate for getting BCF. Being devoid of experiments or abundant experience of the experts, it is very hard to determine the proportional factor accurately. In this paper, an improved PCM (IPCM) is put forward based on the logistic regression model (LRM). The salient features reflecting the equipment degradation process are extracted from the existing monitoring signals, which are considered as the input of the LRM. The equipment state data defined by the failure threshold are considered as the output of the LRM. The initial reliability can be first estimated by LRM. Combined with the responding covariates, the initial hazard function can be calculated. Then, it can be incorporated into conventional PCM to implement the reliability estimation process on other equipment. The conventional PCM and the IPCM methods are respectively applied to aero-engine rotor bearing reliability assessment. The comparative results show that the assessing accuracy of IPCM is superior to the conventional PCM for small failure sample. It provides a new method for reliability estimation under sparse or zero failure data conditions.
      Citation: Machines
      PubDate: 2022-05-05
      DOI: 10.3390/machines10050337
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 338: Bearing Fault Diagnosis via Incremental
           Learning Based on the Repeated Replay Using Memory Indexing (R-REMIND)
           Method

    • Authors: Junhui Zheng, Hui Xiong, Yuchang Zhang, Kaige Su, Zheyuan Hu
      First page: 338
      Abstract: In recent years, deep-learning schemes have been widely and successfully used to diagnose bearing faults. However, as operating conditions change, the distribution of new data may differ from that of previously learned data. Training using only old data cannot guarantee good performance when handling new data, and vice versa. Here, we present an incremental learning scheme based on the Repeated Replay using Memory Indexing (R-REMIND) method for bearing fault diagnosis. R-REMIND can learn new information under various working conditions while retaining older information. First, we use a feature extraction network similar to the Inception-v4 neural network to collect bearing vibration data. Second, we encode the features by product quantization and store the features in indices. Finally, the parameters of the feature extraction and classification networks are updated using real and reconstructed features, and the model did not forget old information. The experiment results show that the R-REMIND model exhibits continuous learning ability with no catastrophic forgetting during sequential tasks.
      Citation: Machines
      PubDate: 2022-05-06
      DOI: 10.3390/machines10050338
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 339: Study on Structural Vibration
           Characteristics of L-Shaped Flexible Ring Gear and Establishment of System
           Coupling Vibration Model

    • Authors: Shengyang Hu, Zongde Fang, Yabin Guan, Xiangying Hou, Chao Liu
      First page: 339
      Abstract: L-shaped flexible ring gear is a new solution to the non-uniform load distribution of planetary transmission systems. At present, the research on L-shaped flexible ring gear is still focused on its meshing characteristics and dynamic load sharing performance, and its structural vibration characteristics and dynamic coupling vibration characteristics with the system are not involved. Considering that the structural flexibility of the L-shaped flexible ring gear is significantly higher than that of the traditional ring gear, the structural vibration will obviously affect the load sharing and dynamic load factor performance of the transmission system, as well as the safety and reliability of the mechanism. Due to its strong structural flexibility and structural particularity, the existing dynamic analysis model is difficult to meet the requirements of analysis and design. In this paper, the coupling vibration model of L-shaped flexible ring gear planetary transmission systems is established, and the structural vibration characteristics of L-shaped flexible ring gear and its influence on the dynamic performance of the systems are deeply analyzed. The model foundation and theoretical guidance are provided for the design of L-shaped flexible ring gear and the analysis of the dynamic characteristics of flexible ring gear systems.
      Citation: Machines
      PubDate: 2022-05-06
      DOI: 10.3390/machines10050339
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 340: Object Detection via Gradient-Based Mask
           R-CNN Using Machine Learning Algorithms

    • Authors: Alphonse Inbaraj Xavier, Charlyn Villavicencio, Julio Jerison Macrohon, Jyh-Horng Jeng, Jer-Guang Hsieh
      First page: 340
      Abstract: Object detection has received a lot of research attention in recent years because of its close association with video analysis and image interpretation. Detecting objects in images and videos is a fundamental task and considered as one of the most difficult problems in computer vision. Many machine learning and deep learning models have been proposed in the past to solve this issue. In the current scenario, the detection algorithm must calculate from beginning to end in the shortest amount of time possible. This paper proposes a method called GradCAM-MLRCNN that combines Gradient-weighted Class Activation Mapping++ (Grad-CAM++) for localization and Mask Regional Convolution Neural Network (Mask R-CNN) for object detection along with machine learning algorithms. In our proposed method, images are used to train the network, together with masks that shows where the objects are in the image. A bounding box is regressed around the region of interest in most localization networks. Furthermore, just like any classification task, the multi-class log loss is minimized during training. This model enhances the calculation time and speed, as well as the efficiency, which recognizes objects in images accurately by comparing state-of-the-art machine learning algorithms, such as decision tree, Gaussian algorithm, k-means clustering, k-nearest neighbor, and logistic regression. Among these methods, we found logistic regression performed well with an accuracy rate of 98.4%, recall rate of 99.6%, and precision rate of 97.3% with respect to ResNet 152 and VGG 19. Furthermore, we proved the goodness of fit of our proposed model using chi-square statistical method and demonstrated that our solution can achieve great precision while maintaining a fair recall level.
      Citation: Machines
      PubDate: 2022-05-06
      DOI: 10.3390/machines10050340
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 341: Investigation on Structural Mapping Laws of
           Sensitive Geometric Errors Oriented to Remanufacturing of Three-Axis
           Milling Machine Tools

    • Authors: Wenzheng Ding, Zhanqun Song, Shuang Ding
      First page: 341
      Abstract: Three-axis milling machine tools are widely used in manufacturing enterprises, and they have enormous potential demands for remanufacturing to improve their performance. During remanufacturing a three-axis milling machine tool, the structure needs to be reconstructed, so it is necessary to identify sensitive geometric errors of the remanufactured machine tool. In the traditional sensitive geometric error identification method, complex error modeling and analysis must be conducted. Therefore, professional knowledge is required, and the process of the identification is cumbersome. This paper focused on the quick identification of sensitive geometric errors for remanufacturing of three-axis milling machine tools. Firstly, sensitive geometric errors of a three-axis milling machine tool were identified based on the multi-body system theory and partial differential method. Then, mapping laws between the sensitive geometric errors and the machine tool structure were firstly presented. According to the proposed mapping laws, the sensitive geometric errors can be identified quickly and easily without complex error modeling and analysis. Finally, the simulation and experiment show that the straightness error of milling is improved up to 0.007 mm by compensating the sensitive geometric errors identified by the proposed mapping laws. The table lookup method based on the mapping laws can quickly identify the sensitive geometric errors of three-axis milling machine tools, which is beneficial for the efficiency and precision of remanufacturing of machine tools.
      Citation: Machines
      PubDate: 2022-05-06
      DOI: 10.3390/machines10050341
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 342: Fault Prediction of Rolling Element Bearings
           Using the Optimized MCKD–LSTM Model

    • Authors: Leilei Ma, Hong Jiang, Tongwei Ma, Xiangfeng Zhang, Yong Shen, Lei Xia
      First page: 342
      Abstract: The reliability and safety of rotating equipment depend on the performance of bearings. For complex systems with high reliability and safety needs, effectively predicting the fault data in the use stage has important guiding significance for reasonably formulating reliability plans and carrying out reliability maintenance activities. Many methods have been used to solve the problem of reliability prediction. Due to its convenience and efficiency, the data-driven method is increasingly widely used in practical reliability prediction. In order to ensure the reliability of bearing operation, the main objective of the present study is to establish a novel model based on the optimized maximum correlation kurtosis deconvolution (MCKD) and long short-term memory (LSTM) recurrent neural network to realize early bearing fault warnings by predicting bearing fault time series. The proposed model is based on the lifecycle vibration signal of the bearing. In the first step, the cuckoo search (CS) is utilized to optimize the parameter filter length and deconvolution period of MCKD, considering the influence of periodic bearing time series, and to improve the fault impact component of the optimized MCKD deconvolution time series. Then the LSTM learning rate is selected according to the deconvolution time series. Finally, the dataset obtained through various preprocessing approaches is used to train and predict the LSTM model. The analyses performed using the XJTU-SY bearing dataset demonstrate that the prediction results are in good consistency with real fault data, and the average prediction accuracy of the optimized MCKD–LSTM model is 26% higher than that of the original time series.
      Citation: Machines
      PubDate: 2022-05-06
      DOI: 10.3390/machines10050342
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 343: A Novel Manual Training Platform for
           Single-Port Laparoscopic Surgery

    • Authors: Mei Feng, Yanlei Gong, Xingze Jin, Zhiwu Han, Ji Zhao, Yan Li
      First page: 343
      Abstract: Single-port minimally invasive surgery requires only a single incision, which further reduced intraoperative bleeding, reduced postoperative pain, and improved cosmetic benefits. However, the cooperative operation of multiple surgical instruments and forming an effective workspace under a single micro-incision remain a great challenge. This paper proposes a new type of manual training platform for single-port minimally invasive surgery. The designed surgical instrument imitates the structure of a human arm. The proximal end of the instrument is deployable structures (such as shoulder joint and elbow joint); they form an operating space and provide stable support for the instrument after deployed. In addition, the distal end of the instrument is a flexible instrument (such as a human hand), to realize posture adjustment and perform surgical operations. The surgical instrument implements a series of synergistic movements from placement, deployment, adjustment, and recovery. In addition, the platform includes a retightening force adjusting mechanism for the tendon-driven method and a quick-change mechanism for surgical instruments. A series of experiments on a functional prototype have validated the effectiveness and reliability of the designed platform. It can be convenient for doctors to practice master–slave single-port surgical instruments in a variety of environments.
      Citation: Machines
      PubDate: 2022-05-06
      DOI: 10.3390/machines10050343
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 344: Measurement and Modelling of a Cycloidal
           Gearbox in Actuator with Permanent Magnet Synchronous Machine

    • Authors: Viktor Šlapák, Jozef Ivan, Karol Kyslan, Matúš Hric, František Ďurovský, Dušan Paulišin, Marek Kočiško
      First page: 344
      Abstract: Compact geared servo drives are a common part of modern industrial automation; thus, their proper modelling is a necessary part for the application and control design. The presented paper focuses on the mathematical model of the cycloidal gearbox, which is used in the compact actuator with a permanent magnet synchronous motor. A measurement procedure to obtain the necessary gearbox parameters is presented along with its mathematical model. A new approach was used to model the stiction and nonlinear gearbox friction behaviour in all four quadrants. A simulation of the actuator with the modelled gearbox is described and its results are compared with the real system measurement. Obtained results show a high match between simulation and experimental results and confirm the correctness of the simulation model.
      Citation: Machines
      PubDate: 2022-05-07
      DOI: 10.3390/machines10050344
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 345: Dynamic Evaluation Method of Straightness
           Considering Time-Dependent Springback in Bending-Straightening Based on
           GA-BP Neural Network

    • Authors: Kong, Yu
      First page: 345
      Abstract: There is a time-dependent springback phenomenon seen during the process of the bending-straightening of slender shafts, which has a great influence on the evaluation of straightness after straightening, creating a risk of misjudgment. This paper presents a dynamic evaluation method of straightness considering time-dependent springback in the bending-straightening process. Firstly, based on viscoelastic mechanics and bending-straightening, the influencing factors of time-dependent springback were analyzed on the basis of certain assumptions, including straightening stroke δC, fulcrum distance L, instantaneous springback δb, straightening time ts, and straightening force Fmax. As the main part of the proposed dynamic evaluation method, the GA-BP neural network is used to establish a model for fast prediction of time-dependent springback in straightening, and it is compared with the linear regression model. The maximum prediction error of the GA-BP model was 0.0038 mm, which was much lower than that of the regression model, at 0.014 mm. The root mean square error (RMSE) of the GA-BP model was 0.0042, and that of the regression model was 0.0098. Finally, the effectiveness of the dynamic straightness evaluation method considering time-dependent springback is verified by experiments. Finally, the sensitivity and relative importance of the influencing factors are analyzed, and the order is δC > ts > Fmax > L > δb.
      Citation: Machines
      PubDate: 2022-05-07
      DOI: 10.3390/machines10050345
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 346: Analysis of Eddy Current Loss of 120-kW
           High-Speed Permanent Magnet Synchronous Motor

    • Authors: Bo Pan, Dajun Tao, Baojun Ge, Likun Wang, Peng Hou
      First page: 346
      Abstract: Pulse width modulation current harmonics and space harmonics are some of the major factors affecting the rotor eddy current loss of the high-speed permanent magnet motor. In this study, based on the principle of the equivalent current sheet, a two-dimensional motor model in a rectangular coordinate system was established. Considering the armature reaction, the end effect, and the current harmonics generated by variable frequency power supply, the eddy current loss of the rotor at different frequencies was analyzed and calculated using the analytical and finite element methods (FEM). When the frequency is between 200 Hz and 600 Hz, the variation trend of the rotor eddy current loss with a frequency obtained by analytical calculation and FEM analysis is roughly the same, and the error is still within a reasonable range. However, as the frequency continues to increase, the error between the two becomes larger and larger. Furthermore, based on the two-dimensional FE model, the influence of the sleeve material, the thickness, and the composite structure on the rotor eddy current loss were studied and analyzed. It was found that adding a graphene shielding layer between the permanent magnet and the sleeve can effectively shield the harmonic magnetic field, greatly reduce the eddy current loss of the permanent magnet, and effectively prevent the temperature of the permanent magnet from being too high, which is conducive to the continuous and stable operation of the high-speed permanent magnet motor.
      Citation: Machines
      PubDate: 2022-05-08
      DOI: 10.3390/machines10050346
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 347: Fault Detection for Interval Type-2 T-S
           Fuzzy Networked Systems via Event-Triggered Control

    • Authors: Zhongda Lu, Chunda Zhang, Fengxia Xu, Zifei Wang, Lijing Wang
      First page: 347
      Abstract: This paper investigates the event-triggered fault diagnosis (FD) problem for interval type-2 (IT2) Takagi–Sugeno (T-S) fuzzy networked systems. Firstly, an FD fuzzy filter is proposed by using IT2 T-S fuzzy theory to generate a residual signal. This means that the FD filter premise variable needs to not be identical to the nonlinear networked systems (NNSs). The evaluation functions are referenced to determine the occurrence of system faults. Secondly, under the event-triggered mechanism, a fault residual system (FRS) is established with parameter uncertainty, external disturbance and time delay, which can reduce signal transmission and communication pressure. Thirdly, the progressive stability of the fault residual system is guaranteed by using the Lyapunov theory. For the energy bounded condition of external noise interference, the performance criterion is established using linear matrix inequalities. The matrix parameters of the target FD filter are obtained by the convex optimization method. A less conservative fault diagnosis method can be obtained. Finally, the simulation example is provided to illustrate the effectiveness and the practicalities of the proposed theoretical method.
      Citation: Machines
      PubDate: 2022-05-08
      DOI: 10.3390/machines10050347
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 348: An Energy Efficiency Tool Path Optimization
           Method Using a Discrete Energy Consumption Path Model

    • Authors: Yicong Gao, Shanghua Mi, Hao Zheng, Qirui Wang, Zhe Wei
      First page: 348
      Abstract: As the energy cost accounts for about one-third of the total manufacturing cost, there is great significance in evaluating and managing energy consumption in manufacturing processes. The energy consumption during multi-axis end milling, which represents a large part of the industrial energy costs, is usually extraordinarily large, especially for complex free-form surfaces requiring multi-finish-machining. To obtain the most efficient tool path, the tool orientation is adjusted to obtain the largest cutting stripe width at each cutter contact point. However, the use of excessive driving energy consumption and cutting energy to obtain the largest cutting stripe width may reduce the energy efficiency of the tool path. To solve this problem, the geometry features of the tool path are analyzed firstly, and the global energy consumption analysis, which includes a cutting energy analysis and driving energy analysis, is conducted. The discrete energy consumption path model is constructed to find the most energy-efficient tool orientation sequence for a tool path. Finally, contrast experiments are carried out to validate the proposed method.
      Citation: Machines
      PubDate: 2022-05-08
      DOI: 10.3390/machines10050348
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 349: A New Parameter Identification Method for
           Industrial Robots with Friction

    • Authors: Bin Kou, Yao Huang, Pengpeng Wang, Dongcheng Ren, Jie Zhang, Shijie Guo
      First page: 349
      Abstract: Commonly used intelligent algorithms that are used to identify the parameters of friction of industrial robots have poor accuracy or involve complex coding, which is not conducive to their use in engineering. This paper uses the random wandering simulated annealing-based variable-step beetle antennae search (RWSAVSBAS) algorithm to identify the parameters of friction of industrial robots. The moment of friction of the third joint of the robot is experimentally obtained and used to establish a Stribeck friction model. Following this, the RWSAVSBAS algorithm is used to identify the frictional parameters of the industrial robot. These parameters can be used to accurately predict the friction-induced torque of the robot.
      Citation: Machines
      PubDate: 2022-05-09
      DOI: 10.3390/machines10050349
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 350: Investigation into the Influence of Parallel
           Offset Wear on Stirling Engine Piston Rod Oil-Free Lubrication Seal

    • Authors: Wenhan Cao, Zhou Chang, Ao Zhou, Xuqiang Dou, Gui Gao, Jun Gong
      First page: 350
      Abstract: The oil-free lubrication seal of a piston rod plays an important role in the application of a Stirling engine. Parallel offset in a piston rod ruins the symmetry of the seal and affects the sealing performance when the seal is worn. In this paper, based on a motion analysis and the finite element method, a three-dimensional model of the Cap-seal was established, and its performance was numerically and experimentally investigated. The results show that parallel offset of the piston rod increases the possibility of seal damage and has no obvious effect on leakage. Under high pressures and low pre-compression ratios, the Cap-seal shows a good sealing capability and exhibits a higher propensity for mechanical damage. A good agreement was obtained between the numerical and experimental results. This study offers guidelines regarding the design and application of oil-free lubrication seals for a Stirling piston rod.
      Citation: Machines
      PubDate: 2022-05-09
      DOI: 10.3390/machines10050350
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 351: COVID-19 Pandemic Response Robot

    • Authors: Min-Fan Ricky Lee, Yi-Ching Christine Chen
      First page: 351
      Abstract: Due to an arising COVID-19 positive confirmed case in Taiwan, the screening of body temperature, mask wearing and quarantined violation is enhanced. A mobile robot that conducts this task is demanded to reduce the human labor. However, conventional robots suffer from several limitations, perceptual aliasing (e.g., different places/objects can appear identical), occlusion (e.g., place/object appearance changes between visits), different viewpoints, the scale of objects, low mobility, less functionality, and some environmental limitations. As for the thermal imager, it displays the current heat spectrum colors, and needs manual monitoring. This paper proposes applying Simultaneous Localization and Mapping in an unknown environment and using deep learning for detection of temperature, mask wearing, and human face on the Raspberry Pi to overcome these problems. It also uses the A* algorithm to do path planning and obstacle avoidance via 3D Light Detection and Ranging to make the robot move more smoothly. Evaluating and implementing different Simultaneous Localization and Mapping algorithms and deep learning models, then selecting the most suitable method. Root Mean Square Error of three Simultaneous Localization and Mapping algorithms are compared. The predictions of deep learning models are evaluated via the metrics (model speed, accuracy, complexity, precision, recall, precision–recall curve, F1 score). In conclusion, Google Cartographer for building a map, Convolutional Neural Network for mask wearing detection, and only looking once for human face detection achieve the best result among all algorithms.
      Citation: Machines
      PubDate: 2022-05-09
      DOI: 10.3390/machines10050351
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 352: An Innovative Pose Control Mechanism for a
           Small Rudderless Underwater Vehicle

    • Authors: Min-Fan Ricky Lee, Yen-Chun Chen
      First page: 352
      Abstract: Current and conventional pose (position and orientation) control of a small underwater vehicle is achieved by using rudders (yaw motion control) and elevators (pitch motion control), but these suffer from non-linear, indirect and complex control issues. This paper proposes an innovative pose control mechanism for small underwater vehicles. The mass shifter mechanism is designed and fabricated to control pitch and yaw motion with a single propeller only. The center of mass of the underwater vehicle is altered by moving a pair of counterweights on fixed tracks. The pitch and yaw are achieved by controlling the position of the counterweight pairs. The proposed system is designed, fabricated and tested in a real underwater environment for proof-of-concept. The result shows a simpler, more efficient and more effective pose control mechanism than conventional technology.
      Citation: Machines
      PubDate: 2022-05-09
      DOI: 10.3390/machines10050352
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 353: Application of Compressed Sensing Based on
           Adaptive Dynamic Mode Decomposition in Signal Transmission and Fault
           Extraction of Bearing Signal

    • Authors: Zhixin Cai, Zhang Dang, Ming Wen, Yong Lv, Haochun Duan
      First page: 353
      Abstract: Bearings are widely used in mechanical equipment; nevertheless, potential dangers are also widespread, making bearing fault detection very important. For large equipment, the amount of collected signals tends to be huge, which challenges both signal transmission and storage. To solve this problem, compressed sensing (CS), based on specific dynamic modes of adaptive truncated rank dynamic mode decomposition (ADMD), is adopted to achieve the purpose of compressing and transmitting the signal, as well as extracting fault features. Firstly, this paper has proposed a new fitness function, which is called the synthetic envelope kurtosis characteristic energy difference ratio, and adopted the improved particle swarm optimization algorithm (IPSO) to select the best truncated rank adaptively. Then, the historical signal attempts to be decomposed into a series of temporal and spatial coherent modes, through ADMD, and those modes are filtered and cascaded into a highly self-adaptive dictionary, the DMD dictionary, which approximates the original signal with some error. Next, CS is employed to compress and reconstruct the signal, in order to reduce storage space and improve transmission efficiency. Finally, signals of high quality can be reconstructed through orthogonal matching pursuit (OMP) algorithm. Compared with traditional dictionaries, the DMD dictionary, based on the mode structure generated by ADMD decomposition, ass proposed in this paper, can better represent the original signal in the simulation signal and have good noise reduction performance. The correlation coefficient (CORR) between the reconstructed signal and noise signal is 0.8109, between the reconstructed signal and non-noise signal is 0.9278, and the root mean square error (RMSE) is 0.0659 and 0.0351, respectively. Compared with the traditional SVD and EMD denoising methods, ADMD-CS has better noise reduction performance. In this paper, the signal-to-noise ratio (SNR) is taken as the quantitative indicator of denoising performance. It is found that the SNR of simulation signal and experimental signal processed by ADMD-CS is higher than that of the traditional denoising methods, which is 0.3017 and 0.8407, respectively. The storage space of the signal is quite smaller than traditional methods, and the compression ratios (CR) of the simulation and experimental signals are 66.16% and 59.08%, respectively. In conclusion, ADMD-CS has a good application prospect in signal transmission, storage, and feature extraction.
      Citation: Machines
      PubDate: 2022-05-09
      DOI: 10.3390/machines10050353
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 354: On-Line Detection of Demagnetization for
           Permanent Magnet Synchronous Motor via Flux Observer

    • Authors: Liqian Cao, Zhong Wu
      First page: 354
      Abstract: Demagnetization in permanent magnet synchronous motor (PMSM), caused by high temperature or inverse magnetic field, may increase loss and torque ripple, and even degrade the system stability in severe cases. On-line detection can identify the incipient demagnetization of permanent magnets (PMs), as well as providing reference for subsequent fault-tolerant control, so as to avoid further demagnetization. Therefore, an on-line demagnetization detection method is proposed in this paper by using flux observer. First, an observer is established in the three-phase stationary reference frame by taking the stator currents and the amplitudes of the fundamental and harmonic components of flux as state variables. Then, three demagnetization indexes are presented to evaluate the properties of PMs based on the observed flux information. The proposed method can directly track the amplitude of harmonic flux and evaluate the severity of the demagnetization more comprehensively. Simulation and experimental results demonstrate the effectiveness of the proposed method.
      Citation: Machines
      PubDate: 2022-05-09
      DOI: 10.3390/machines10050354
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 355: Numerical and Experimental Analysis for the
           Dynamics of Flawed–Machining Rod–Disk Rotor with Inner
           Misalignment

    • Authors: Xin Jin, Yi Liu
      First page: 355
      Abstract: The nonlinear dynamic effects of the misalignment between inner disks in a flawed–machining rod–disk rotor is studied. Non–uniform stress distribution due to inner misalignment is obtained based on 3D static solution. The concomitant unbalances, including constant mass eccentricity and speed–variant rotor bending, are taken into account in the nonlinear dynamics. The dynamic results show that rotor bending leads to stability reduction and vibration growth. There is a distinctive feature in that the rotor’s vibration goes up again after critical speed. The maximum allowable inner misalignment is obtained according to its stability boundaries. An uneven tightening method is also presented to reduce adverse effects when the inner misalignment exists. Moreover, an experiment is designed to measure the vibration characteristics for the rod–disk rotor bearing system with inner misalignment. The results show that the theoretical result of vibration amplitude of the flawed rod–rotor bearing system is basically consistent with the experimental value. It is also found that the precise rotor performs the periodic motion, but the flawed rod–disk rotor exhibits the period–doubling orbit. This phenomenon proves that the flawed rod–disk rotor loses stability more easily than the precise rotor due to inner misalignment. However, the amplitude of harmonic frequency components for the precise rod–disk rotor system is obviously larger than the flawed rod–disk rotor system with inner misalignment. The peak value of the vibration amplitude increases when the inner misalignment becomes larger. On the whole, this work presents numerical and experimental analysis to study the dynamics of flawed-machining rod–disk rotor with inner misalignment. It also establishes the relationship between centration precision and dynamic features.
      Citation: Machines
      PubDate: 2022-05-09
      DOI: 10.3390/machines10050355
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 356: Natural Frequency Degradation Prediction for
           Offshore Wind Turbine Structures

    • Authors: Gwanghee Park, Dayoung You, Ki-Yong Oh, Woochul Nam
      First page: 356
      Abstract: The scale of offshore wind turbines (OWTs) has increased in order to enhance their energy generation. However, strong aero/hydrodynamic loads can degrade the dynamic characteristics of OWTs because they are installed on soft seabeds. This degradation can shorten the structural life of the system; repetitive loads lead to seabed softening, reducing the natural frequency of the structure close to the excitation frequency. Most of the previous studies on degradation trained prediction algorithms with actual sensor signals. However, there are no actual sensor data on the dynamic response of OWTs over their lifespan (approximately 20 years). In order to address this data issue, this study proposes a new prediction platform combining a dynamic OWT model and a neural network-based degradation prediction model. Specifically, a virtual dynamic response was generated using a three-dimensional OWT and a seabed finite element model. Then, the LSTM model was trained to predict the natural frequency degradation using the dynamic response as the model input. The results show that the developed model can accurately predict natural frequencies over the next several years using past and present accelerations and strains. In practice, this LSTM model could be used to predict future natural frequencies using the dynamic response of the structure, which can be measured using actual sensors (accelerometers and strain gauges).
      Citation: Machines
      PubDate: 2022-05-10
      DOI: 10.3390/machines10050356
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 357: Research on the Controllable Interface
           Response Enhancement of the Textured Pilot Valve

    • Authors: Jing Xu, Guiming Zhang, Shaochao Fan, Jing Ni, Jiadi Lian
      First page: 357
      Abstract: Based on the textured controllable interface effect, the dynamic performances of the textured and ordinary pilot valve are analyzed experimentally, and the influence of the textured controllable interface on the response of pilot valve is studied. Results show that when Pin is small, the textured surface shortens the reciprocating time of valve core, increasing the flow rate, and speeds up the piston stroke of oil cylinder. The valve core actions much more stable and sensitivity. Meanwhile, combined with the theoretical calculation, the operation mechanism of texturing the pilot valve is analyzed. It is concluded that the stress of textured valve core sealing surface is greater than that of ordinary one, and the pressure difference gradually decreases with the increase in Pin, and the flow difference is basically the same as the force on the sealing surface. This indicates that the textured surface improves lubrication characteristics, reduces the friction between components. The textured valve makes the velocity changes gently, and enhances the responsiveness and stability of the valve. Those related results provide a new idea for enhancing the response design of the pilot valve.
      Citation: Machines
      PubDate: 2022-05-10
      DOI: 10.3390/machines10050357
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 358: Full Factorial Simulation Test Analysis and
           I-GA Based Piecewise Model Comparison for Efficiency Characteristics of
           Hydro Mechanical CVT

    • Authors: Zhun Cheng, Yuting Chen, Wenjie Li, Junhao Liu, Li Li, Pengfei Zhou, Wenjuan Chang, Zhixiong Lu
      First page: 358
      Abstract: The hydro-mechanical continuously variable transmission (HMCVT) has complicated transmission characteristics. To analyze the influences of various factors on HMCVT’s efficiency characteristics and build a more precise HMCVT efficiency characteristic model, the paper conducted a full factorial simulation test for and a modeling study on a novel five-stage HMCVT’s efficiency characteristics. The full factorial test considered four factors with a total of 160 groups of test samples and used a range analysis method. Moreover, we proposed a piecewise modeling method for HMCVT efficiency characteristics based on the improved genetic algorithm (I-GA) and compared the precision of seven models. Research results showed that the working stage with the power output from the planet carrier had relatively higher efficiency. The variable pump’s displacement ratio had the greatest influence, and the HMCVT’s efficiency characteristics presented two variation laws with the boundary that the displacement ratio is 0. The load power and the engine speed showed a positive correlation and a negative correlation with the efficiency characteristics, respectively, and the influences decreased as the factor values increased. The modeling method proposed had high modeling precision and the mean absolute percentage error (MAPE) of seven models was in the range of 1.6884~3.1375%. The estimation precision greatly could be improved (the MAPE reduced by 7.7024% and the R2 increased by 9.2943%) by introducing the first-order term of engine speed on the basis of a two-factor model (in which the factors were the displacement ratio and the load power). The paper aimed to offer direct reference information on parameters of the mechanical design and control strategy development of HMCVT from an energy-saving perspective in the design stage.
      Citation: Machines
      PubDate: 2022-05-10
      DOI: 10.3390/machines10050358
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 359: Effect of Inlet Condition on the Performance
           Curve of a 10 MW Supercritical Carbon Dioxide Centrifugal Compressor

    • Authors: Zhiting Tong, Xiaomin Yang, Pengxu Shang, Jingyuan Ma, Yue Zhang, Chao Zhang
      First page: 359
      Abstract: The influence of inlet condition upon the performance and stability for a 10 MW supercritical carbon dioxide centrifugal compressor is investigated using the computational fluid dynamics method. The inlet conditions which are considered are as follows, a constant inlet pressure of 8.0 MPa with varying inlet temperatures of 308.15 K, 308 K, 306 K, and 304 K, and a fixed inlet temperature of 308.15 K with different inlet pressures of 7.5 MPa, 8.0 MPa and 8.5 MPa. The numerical method with the k-omega based shear-stress-transport turbulence model is validated compared to the published experimental data. The numerical result shows that a small variation of temperature or pressure significantly has huge impact on the compressor performance operating near the critical point of supercritical carbon dioxide. As the compressor inlet pressure increases, the compression factor of the working fluid becomes lower, resulting in an enlargement of the pressure ratio. However, the decrease in inlet temperature leads to a higher compression factor of the working fluid and a reduced pressure ratio. The variation of the isentropic efficiency curve is mainly attributed to the change in the compressor inlet volumetric flow rate. The locations of the stall point and choke point are dependent on the values of inlet pressure and temperature.
      Citation: Machines
      PubDate: 2022-05-10
      DOI: 10.3390/machines10050359
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 360: Functional Safety Analysis and Design of
           Sensors in Robot Joint Drive System

    • Authors: Lingyu Chen, Dapeng Fan, Jieji Zheng, Xin Xie
      First page: 360
      Abstract: The reliable operation of the sensors of robot joint drive systems (RJDs) is a key factor in ensuring the safety of equipment and personnel. Over the years, additional safety-related systems have been designed to prevent safety incidents caused by robot failures, ignoring the functional safety issues of the robot sensors themselves. In view of this, based on IEC61508, a functional safety analysis and design method for sensors of RJDs is proposed in this paper. Firstly, the hazard analysis and risk assessment clarified the goals that the safety protection function of the RJD’s sensor should achieve. Then, by establishing the motor drive model and transmission model, a model-based sensor fault diagnosis and isolation strategy is proposed. Considering the fault-tolerant operation of system, a fail-operational hardware architecture of the safety-related system is designed. Markov analysis shows that the safety integrity level (SIL) of safety-related systems can reach SIL3. Finally, experiments are designed to validate the proposed fault diagnosis and fault tolerance strategy. The results show that the safety-related system can effectively locate sensor failures, realize fault-tolerant control when a single sensor fails and perform safe torque off (STO) protection when multiple sensors fail.
      Citation: Machines
      PubDate: 2022-05-10
      DOI: 10.3390/machines10050360
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 361: A Novel Electronic Chip Detection Method
           Using Deep Neural Networks

    • Authors: Huiyan Zhang, Hao Sun, Peng Shi, Luis Ismael Minchala
      First page: 361
      Abstract: Electronic chip detection is widely used in electronic industries. However, most existing detection methods cannot handle chip images with multiple classes of chips or complex backgrounds, which are common in real applications. To address these problems, a novel chip detection method that combines attentional feature fusion (AFF) and cosine nonlocal attention (CNLA), is proposed, and it consists of three parts: a feature extraction module, a region proposal module, and a detection module. The feature extraction module combines an AFF-embedded CNLA module and a pyramid feature module to extract features from chip images. The detection module enhances feature maps with a region intermediate feature map by spatial attentional block, fuses multiple feature maps with a multiscale region of the fusion block of interest, and classifies and regresses objects in images with two branches of fully connected layers. Experimental results on a medium-scale dataset comprising 367 images show that our proposed method achieved mAP0.5=0.98745 and outperformed the benchmark method.
      Citation: Machines
      PubDate: 2022-05-10
      DOI: 10.3390/machines10050361
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 362: Development of a Two-Dimensional Ultrasonic
           Device for Vibration-Assisted Milling

    • Authors: Engy Osama Rashed, Adel Nofal, Ahmed H. Abd EI-Malek, Mohab Hossam
      First page: 362
      Abstract: Two-dimensional vibration-assisted machining (VAM) is a technique used to improve the cutting performance of machining processes by reducing the cutting forces and the temperature, extending the tool life, and improving the surface quality. Among the developed 2D vibratory devices for VAM, some limitations affect the process stability. This paper aims to present a 2D vibratory device to be applied during the milling process with a setup structure overcoming the limitations of the other developed devices. The device operates at high vibration frequency, prevents the coupling effect problem, provides precise vibration motion, and is easily manufactured, assembled, installed, and maintained. Finite element analysis (FEA) was applied to verify and modify the proposed design. The components of the final design were manufactured, and the generated vibration in each direction was evaluated. A detailed control system was presented to maintain the stability for the applied vibration. Finally, slot-milling experiments were conducted to validate and test the device’s performance. The cutting experiments results showed some benefits of applying the ultrasonic vibration and validated that the 2D vibratory device is functioning properly.
      Citation: Machines
      PubDate: 2022-05-10
      DOI: 10.3390/machines10050362
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 363: Improved DBSCAN Spindle Bearing Condition
           Monitoring Method Based on Kurtosis and Sample Entropy

    • Authors: Yanfei Zhang, Yunhao Li, Lingfei Kong, Qingbo Niu, Yu Bai
      First page: 363
      Abstract: An improved density-based spatial clustering of applications with noise (IDBSCAN) analysis approach based on kurtosis and sample entropy (SE) is presented for the identification of operational state in order to provide accurate monitoring of spindle operation condition. This is because of the low strength of the shock signal created by bearing of precision spindle of misalignment or imbalanced load, and the difficulties in extracting shock features. Wavelet noise reduction begins by dividing the recorded vibration data into equal lengths. Features like kurtosis and entropy in the frequency domain are used to generate feature vectors that indicate the bearing operation state. IDBSCAN cluster analysis is then utilized to establish the ideal neighborhood radius (Eps) and the minimum number of objects contained within the neighborhood radius (MinPts) of the vector set, which are combined to identify the bearing operating condition features. Finally, utilizing data from the University of Cincinnati, the approach was validated and assessed, attaining a condition detection accuracy of 99.2%. As a follow-up, the spindle’s vibration characteristics were studied utilizing an unbalanced bearing’s load bench. Bearing state recognition accuracy was 98.4%, 98.4%, and 96.7%, respectively, under mild, medium, and overload circumstances, according to the results of the experimental investigation. Moreover, it shows that conditions of bearings under various unbalanced loads can be precisely monitored using the proposed method without picking up on specific sorts of failures.
      Citation: Machines
      PubDate: 2022-05-10
      DOI: 10.3390/machines10050363
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 364: Autonomous Visual Navigation for a Flower
           Pollination Drone

    • Authors: Dries Hulens, Wiebe Van Van Ranst, Ying Cao, Toon Goedemé
      First page: 364
      Abstract: In this paper, we present the development of a visual navigation capability for a small drone enabling it to autonomously approach flowers. This is a very important step towards the development of a fully autonomous flower pollinating nanodrone. The drone we developed is totally autonomous and relies for its navigation on a small on-board color camera, complemented with one simple ToF distance sensor, to detect and approach the flower. The proposed solution uses a DJI Tello drone carrying a Maix Bit processing board capable of running all deep-learning-based image processing and navigation algorithms on-board. We developed a two-stage visual servoing algorithm that first uses a highly optimized object detection CNN to localize the flowers and fly towards it. The second phase, approaching the flower, is implemented by a direct visual steering CNN. This enables the drone to detect any flower in the neighborhood, steer the drone towards the flower and make the drone’s pollinating rod touch the flower. We trained all deep learning models based on an artificial dataset with a mix of images of real flowers, artificial (synthetic) flowers and virtually rendered flowers. Our experiments demonstrate that the approach is technically feasible. The drone is able to detect, approach and touch the flowers totally autonomously. Our 10 cm sized prototype is trained on sunflowers, but the methodology presented in this paper can be retrained for any flower type.
      Citation: Machines
      PubDate: 2022-05-10
      DOI: 10.3390/machines10050364
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 365: Obstacle Modeling and Structural
           Optimization of Four-Track Twin-Rocker Rescue Robot

    • Authors: Xiaobin Xu, Wen Wang, Guangyu Su, Cong Liu, Wei Cai, Haojie Zhang, Yingying Ran, Zhiying Tan, Minzhou Luo
      First page: 365
      Abstract: In order to achieve the best obstacle surmounting performance of a mobile robot in the rescue environment, a four-track twin-rocker bionic rescue robot with an inner and outer concentric shaft was designed in this paper. From the viewpoint of dynamics, the motion process of the mass center of the robot when climbing steps forward and backward was studied. The maximum obstacle height of the robot was calculated. The relationship between the elevation angle of the car body, the swing angle of the rocker arm and the height of the steps was analyzed by simulation. The simulation results show that the maximum forward and reverse obstacle crossing heights were 92.99 mm and 155.82 mm, respectively. Obstacle climbing experiments of the designed robot prototype were carried out. It was found that the measured maximum height of the step was 95 mm, and the measured maximum height of the reverse obstacle was 165 mm. Finally, bionic particle swarm optimization was used to optimize the structural parameters of the rocker arm with an optimal length of 315.2 mm. The study of this paper can be referenced for the design and analysis of obstacle surmounting rescue robots with similar structures.
      Citation: Machines
      PubDate: 2022-05-10
      DOI: 10.3390/machines10050365
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 366: Distributed Dynamic Predictive Control for
           Multi-AUV Target Searching and Hunting in Unknown Environments

    • Authors: Juan Li, Chengyue Li, Honghan Zhang
      First page: 366
      Abstract: The research and development of the ocean has been gaining in popularity in recent years, and the problem of target searching and hunting in the unknown marine environment has been a pressing problem. To solve this problem, a distributed dynamic predictive control (DDPC) algorithm based on the idea of predictive control is proposed. The task-environment region information and the input of the AUV state update are obtained by predicting the state of multi-AUV systems and making online task optimization decisions and then locking the search area for the following moment. Once a moving target is found in the search process, the AUV conducts a distributed hunt based on the theory of potential points, which solves the problem of the reasonable distribution of potential points during the hunting process and realizes the formation of hunting rapidly. Compared with other methods, the simulation results show that the algorithm exhibits high efficiency and adaptability.
      Citation: Machines
      PubDate: 2022-05-11
      DOI: 10.3390/machines10050366
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 367: Digital Twins-Based Production Line Design
           

    • Authors: Rongli Zhao, Guangxin Zou, Qianyi Su, Shangwen Zou, Wenshun Deng, Ailin Yu, Hao Zhang
      First page: 367
      Abstract: The mobile phone is a typical 3C electronic product characterized by frequent replacement, multiple product specifications, high flexibility, high-frequency production line switching, and urgent delivery time during production. Therefore, the optimized design of the mobile phone production workshop is crucial. This paper takes the assembly process of a specific type of mobile phone assembly as the research object and adopts the heuristic balance method to combine the production procedures. Moreover, it considers the automation degree of the process and the demand for production line rhythm to carry out station division and working hours design for the assembly process. The advantages and disadvantages of the plug-and-play production line and unit production line architecture are integrated, aiming at the production line’s construction cost and unit area capacity. A hybrid workshop with a mixed combination of two types of production lines is designed and an optimization model of hybrid workshop design is established. The semi-physical simulation technology of digital twins is utilized to verify the proposed design scheme to achieve the balance optimization of the production line, improve production efficiency, and reduce production costs. This work provides a technical scheme for designing and optimizing large-scale mobile phone assembly workshops with multi-batch and high-frequency production changes.
      Citation: Machines
      PubDate: 2022-05-11
      DOI: 10.3390/machines10050367
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 368: Stress Characteristics Analysis of Vertical
           Bi-Directional Flow Channel Axial Pump Blades Based on
           Fluid–Structure Coupling

    • Authors: Xinyi Liu, Fengyang Xu, Li Cheng, Weifeng Pan, Weixuan Jiao
      First page: 368
      Abstract: The RANS equation and the RNG k-ε turbulence model were used in the three-dimensional non-constant numerical simulations of the full flow path of a vertical axial-flow pump which was carried out by applying CFX software. The velocity characteristics of the flow field and the pressure distribution of the impeller under different operating conditions were analyzed and verified by external characteristic tests. The fluid–structure interaction research was conducted for the stress distribution and deformation features of different surfaces of the blade under different working conditions. The result shows that where stress is most concentrated is at the point of the root of the blade near the hub. The low-pressure zone on the suction surface is mainly distributed near the rim, and the low-pressure area on the pressure side is mainly distributed near the hub.
      Citation: Machines
      PubDate: 2022-05-12
      DOI: 10.3390/machines10050368
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 369: A Two-Stage Transfer Regression
           

    • Authors: Xianling Li, Kai Zhang, Weijun Li, Yi Feng, Ruonan Liu
      First page: 369
      Abstract: Recently, deep learning techniques have been successfully used for bearing remaining useful life (RUL) prediction. However, the degradation pattern of bearings can be much different from each other, which leads to the trained model usually not being able to work well for RUL prediction of a new bearing. As a method that can adapt a model trained on source datasets to a different but relative unlabeled target dataset, transfer learning shows the potential to solve this problem. Therefore, we propose a two-stage transfer regression (TR)-based bearing RUL prediction method. Firstly, the incipient fault point (IFP) is detected by a convolutional neural network (CNN) classifier to identity the start time of degradation stage and label the training samples. Then, a transfer regression CNN with multiloss is constructed for RUL prediction, including regression loss, classification loss, maximum mean discrepancy (MMD) and regularization loss, which can not only extract fault information from fault classification loss for RUL prediction, but also minimize the probability distribution distance, thus helping the method to be trained in a domain-invariant way via the transfer regression algorithm. Finally, real data collected from run-to-failure bearing experiments are analyzed by the TR-based CNN method. The results and comparisons with state-of-the-art methods demonstrate the superiority and reliable performance of the proposed method for bearing RUL prediction.
      Citation: Machines
      PubDate: 2022-05-12
      DOI: 10.3390/machines10050369
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 370: Study of the Self-Locking Characteristics of
           the Swing Scraper of an Elliptical Rotor Scraper Pump

    • Authors: Yang Cao, Tiezhu Zhang, Hongxin Zhang, Zhen Zhang, Jian Yang, Baoquan Liu
      First page: 370
      Abstract: This paper proposes an Elliptical Rotor Scraper Pump (ERSP) to address traditional displacement pump defects, such as complex structures, poor self-sealing, low volume utilization, and considerable noise, etc. The ERSP utilizes a swing scraper instead of one rotor in a conventional multirotor pump or reciprocating moving vanes in a traditional vane pump and can achieve high-pressure output through pressure self-sealing. The swing scraper can divide the working chamber into high- and low-pressure rooms. Due to the small swing amplitude of the scraper, the ERSP has low operating noise. The ERSP rotor with an elliptical shape can significantly improve pump volume utilization, thus, forming a kind of fluid pump without a distribution valve, high pressure, and compact structure, and can work efficiently at high speed. This paper establishes a three-dimensional model and mathematical model for the ERSP, then develops the mathematical relationship between the scraper rotation angle and rotor rotation angle and carries out the simulation analysis based on MSC ADAMS. Then, the self-locking characteristics of the ERSP are studied through a force analysis of the swing scraper. Finally, our research group designs and produces a prototype based on existing research and verifies the superiority of the ERSP and the correctness of the non-self-locking condition through experiments. The results in this paper provide a reference for research on the self-locking characteristics of fluid rotor pumps and engineering optimization, which has great significance to the development of fluid power machinery.
      Citation: Machines
      PubDate: 2022-05-13
      DOI: 10.3390/machines10050370
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 371: A Compatible Design of a Passive Exoskeleton
           to Reduce the Body–Exoskeleton Interaction Force

    • Authors: Nengbing Zhou, Yali Liu, Qiuzhi Song, Dehao Wu
      First page: 371
      Abstract: In the research and development of a passive exoskeleton, the body–exoskeleton coupling mode is a key point to reduce the interaction force and realize the efficient assistance of the exoskeleton. The purpose of this paper was to explore a cooperative movement mode between human and passive exoskeleton for reducing the body–exoskeleton interaction force. Firstly, through the research of the body–exoskeleton interactive mode, we analyzed the kinematic and dynamic constraint of the exoskeleton and established a dynamic model of the body–exoskeleton system. On this basis, the characteristic of the body–exoskeleton interaction force was analyzed; then, we put forward a mode that uses human gravity and load weight to maintain the stability of the exoskeleton’s movement to achieve the goal of reducing the interaction force. Based on the human–exoskeleton integrated mode, we constructed a mechanical model and simulated the change in interaction force in this mode; the simulation results showed that the interaction force at the lower leg was 98.5% less than that of the pure mechanical exoskeleton. Finally, we developed a prototype that was made of plastic parts and finished the experiment by walking with a load of 30 kg. The experimental results showed that this mode reduced the body–exoskeleton interaction force by 65.1%, which verified the effectiveness of the body–exoskeleton coupling mode preliminarily. The research results provided a new analytical approach for the design of a passive exoskeleton, and its improvement effect could be extended from the lower leg of the body–exoskeleton to the thigh or trunk, and guide the design of a passive exoskeleton.
      Citation: Machines
      PubDate: 2022-05-13
      DOI: 10.3390/machines10050371
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 372: High-Precision Laboratory Dryer for
           

    • Authors: Sebastian Reyer, Sebastian Awiszus, Joachim Müller
      First page: 372
      Abstract: To reduce the energy consumption during the drying of agricultural and food products, the optimization of the drying process with regard to the drying behavior and the quality of the end products is necessary. Therefore, much effort is spent designing and developing dryers to study the drying behavior of a wide range of products. This often results in a trade-off between measurement accuracy and the sufficient production of dried material required for the product quality analysis. Therefore, a laboratory dryer was developed consisting of three high-precision drying columns, each able to process 600 g of sample mass, and a flatbed dryer that can be loaded with 20 kg of fresh product. Drying curves could be recorded simultaneously by electronic balances in the three precision dryers and the flatbed dryer. The high-precision laboratory dryer HPD TF3+ proved to be suitable for establishing drying curves for a defined temperature, rel. humidity and velocity of the drying air.
      Citation: Machines
      PubDate: 2022-05-13
      DOI: 10.3390/machines10050372
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 373: A New Piecewise Nonlinear Asymmetry Bistable
           Stochastic Resonance Model for Weak Fault Extraction

    • Authors: Li Cui, Wuzhen Xu
      First page: 373
      Abstract: In order to solve output saturation problems found in traditional stochastic resonance methods and to improve the diagnosis ability of weak faults, a new piecewise nonlinear asymmetric bistable stochastic resonance (PNABSR) method is proposed. This model uses a left and right potential function with an asymmetrical shape, which makes it easier to induce stochastic resonance phenomena. Based on the PNABSR model, the expression of the signal-to-noise ratio (SNR) is derived, and the changes in the SNR with different parameters in the PNABSR model are analyzed. Then, the parameters in the PNABSR model are optimized using the adaptive intelligent algorithm to enhance the diagnostic ability. The diagnosis properties of the weak fault are compared between the PNABSR model and the classical bistable stochastic resonance model (CBSR). The experimental results prove that the PNABSR model can effectively extract the weak fault characteristic frequency under a strong noise background, verifying the effectiveness of this method.
      Citation: Machines
      PubDate: 2022-05-14
      DOI: 10.3390/machines10050373
      Issue No: Vol. 10, No. 5 (2022)
       
  • Machines, Vol. 10, Pages 274: Analysis and Verification of the Method of
           Improving Inductance by Magnetic Endcaps in Slotless Permanent Magnet
           Motor

    • Authors: Chenglong Chu, Yunkai Huang
      First page: 274
      Abstract: The slotless permanent magnet motor (SPMM) has low phase inductance due to the larger physical air gap, which will adversely affect motor control and current harmonics. In this paper, the method of forming an extra magnetic circuit by endcap around the outer stator is proposed. The advantage of this method is that a restrained flux path is formed without increasing the motor structure and cost, and the inductance of the motor is effectively improved without causing a significant decrease in torque. The preliminary simulation analysis and corresponding experimental content are carried out. The experimental results and the simulation content showed good consistency, which verified the correctness of the theory and simulation analysis.
      Citation: Machines
      PubDate: 2022-04-12
      DOI: 10.3390/machines10040274
      Issue No: Vol. 10, No. 4 (2022)
       
  • Machines, Vol. 10, Pages 275: Integration of Design, Manufacturing, and
           Service Based on Digital Twin to Realize Intelligent Manufacturing

    • Authors: Luyao Zhang, Lijie Feng, Jinfeng Wang, Kuo-Yi Lin
      First page: 275
      Abstract: Complex product design, manufacturing, and service are the key elements of a product’s life cycle. However, the traditional manufacturing processes of design, manufacturing, and service are independent of each other, so lack deep integration. The emergence of digital twins offers an opportunity to accelerate the integration of complex product design, manufacturing, and services. For intelligent manufacturing, physical entity and virtual entity transformation can be realized through digital information. A collaborative framework for complex product design, manufacturing, and service integration based on digital twin technology was proposed. The solutions of process integration, data flow, modeling and simulation, and information fusion were analyzed. The core characteristics and key technologies of service-oriented manufacturing, design for service and manufacturing, and manufacturing monitoring based on the deep integration of the digital twin were discussed. Finally, the feasibility of the framework was verified by a self-balancing multistage pump manufacturing case. The performance of the upgraded pump under the framework was tested, and the test results proved the effectiveness of the integrated framework.
      Citation: Machines
      PubDate: 2022-04-12
      DOI: 10.3390/machines10040275
      Issue No: Vol. 10, No. 4 (2022)
       
  • Machines, Vol. 10, Pages 276: Velocity and Singularity Analysis of a 5-DOF
           (3T2R) Parallel-Serial (Hybrid) Manipulator

    • Authors: Pavel Laryushkin, Anton Antonov, Alexey Fomin, Terence Essomba
      First page: 276
      Abstract: This article presents the velocity and singularity analysis for a five-degree-of-freedom (5-DOF) parallel-serial manipulator. The hybrid structure of the manipulator combines a tripod-like parallel part and a serial part, represented as two carriages moving in perpendicular directions. This manipulator provides its end-effector with a 3T2R motion pattern, which includes three independent translations and two independent rotations. First, the study briefly discusses the manipulator design and the results of the position analysis. These results form the basis for the subsequent velocity and singularity analysis, performed by screw theory. The screw coordinates of the unit twists are written for each manipulator joint, and then through the reciprocal screw approach, the actuation and constraint wrenches of the manipulator are obtained by simple inspection. Based on these twists and wrenches, the paper forms the velocity equation and shows an example of the inverse velocity analysis for a given end-effector trajectory. The same example is solved by numerical differentiation to verify the proposed approach. Next, the paper investigates singular configurations by analyzing the wrench system of the manipulator and presents several conditions for serial and parallel singularities. Each condition has both a symbolic representation, given by an equation for screw coordinates of certain wrenches, and a visual representation, which shows the manipulator in a singular configuration.
      Citation: Machines
      PubDate: 2022-04-13
      DOI: 10.3390/machines10040276
      Issue No: Vol. 10, No. 4 (2022)
       
  • Machines, Vol. 10, Pages 277: Improved DCNN Based on Multi-Source Signals
           for Motor Compound Fault Diagnosis

    • Authors: Xiaoyun Gong, Zeheng Zhi, Kunpeng Feng, Wenliao Du, Tao Wang
      First page: 277
      Abstract: Induction motors, the key equipment for rotating machinery, are prone to compound faults, such as a broken rotor bars and bearing defects. It is difficult to extract fault features and identify faults from a single signal because multiple fault features overlap and interfere with each other in a compound fault. Since current signals and vibration signals have different sensitivities to broken rotor and bearing faults, a multi-channel deep convolutional neural network (MC-DCNN) fault diagnosis model based on multi-source signals is proposed in this paper, which integrates the original signals of vibration and current of the motor. Dynamic attenuation learning rate and SELU activation function were used to improve the network hyperparameters of MC-DCNN. The dynamic attenuated learning rate can improve the stability of model training and avoid model collapse effectively. The SELU activation function can avoid the problems of gradient disappearance and gradient explosion during model iteration due to its function configuration, thereby avoiding the model falling into local optima. Experiments showed that the proposed model can effectively solve the problem of motor compound fault identification, and three comparative experiments verified that the improved method can improve the stability of model training and the accuracy of fault identification.
      Citation: Machines
      PubDate: 2022-04-14
      DOI: 10.3390/machines10040277
      Issue No: Vol. 10, No. 4 (2022)
       
  • Machines, Vol. 10, Pages 278: A Fast Method for Protecting Users’
           Privacy in Image Hash Retrieval System

    • Authors: Liang Huang, Yu Zhan, Chao Hu, Ronghua Shi
      First page: 278
      Abstract: Effective search engines based on deep neural networks (DNNs) can be used to search for many images, as is the case with the Google Images search engine. However, the illegal use of search engines can lead to serious compromises of privacy. Affected by various factors such as economic interests and service providers, hackers and other malicious parties can steal and tamper with the image data uploaded by users, causing privacy leakage issues in image hash retrieval. Previous work has exploited the adversarial attack to protect the user’s privacy with an approximation strategy in the white-box setting, although this method leads to slow convergence. In this study, we utilized the penalty norm, which sets a strict constraint to quantify the feature of a query image into binary code via the non-convex optimization process. Moreover, we exploited the forward–backward strategy to solve the vanishing gradient caused by the quantization function. We evaluated our method on two widely used datasets and show an attractive performance with high convergence speed. Moreover, compared with other image privacy protection methods, our method shows the best performance in terms of privacy protection and image quality.
      Citation: Machines
      PubDate: 2022-04-14
      DOI: 10.3390/machines10040278
      Issue No: Vol. 10, No. 4 (2022)
       
  • Machines, Vol. 10, Pages 279: A New Framework for the Harmonic Balance
           Method in OpenFOAM

    • Authors: Stefano Oliani, Nicola Casari, Mauro Carnevale
      First page: 279
      Abstract: The Harmonic Balance Method is one of the most commonly employed Reduced Order Models for turbomachinery calculations, since it leverages the signal sparsity in the frequency domain to cast the transient equations into a coupled set of steady-state ones. The present work aims at detailing the development and validation of a new framework for the application of the Harmonic Balance Method in the open-source software OpenFOAM. The paper is conceptually divided into building blocks for the implementation of the code. For each of these, theoretical notions and coding strategies are given, and an ad hoc validation test case is presented. This structure has been chosen with the aim of easing the reader in the understanding and implementation of such a method in a generic fluid dynamics solver. In a fully open source philosophy, the library files are freely accessible in the authors’ repository (link provided below in the text).
      Citation: Machines
      PubDate: 2022-04-14
      DOI: 10.3390/machines10040279
      Issue No: Vol. 10, No. 4 (2022)
       
  • Machines, Vol. 10, Pages 280: Experimental Characterization of A-AFiM, an
           Adaptable Assistive Device for Finger Motions

    • Authors: Jhon Freddy Rodríguez-León, Eduardo Castillo-Castañeda, José Felipe Aguilar-Pereyra, Giuseppe Carbone
      First page: 280
      Abstract: Robot rehabilitation devices are attracting significant research interest, aiming at developing viable solutions for increasing the patient’s quality of life and enhancing clinician’s therapies. This paper outlines the design and implementation of a low-cost robotic system that can assist finger motion rehabilitation by controlling and adapting both the position and velocity of fingers to the users′ needs. The proposed device consists of four slider-crank mechanisms. Each slider-crank is fixed and moves one finger (from the index to the little finger). The finger motion is adjusted through the regulation of a single link length of the mechanism. The trajectory that is generated corresponds to the natural flexion and extension trajectory of each finger. The functionality of this mechanism is validated by experimental image processing. Experimental validation is performed through tests on healthy subjects to demonstrate the feasibility and user-friendliness of the proposed solution.
      Citation: Machines
      PubDate: 2022-04-15
      DOI: 10.3390/machines10040280
      Issue No: Vol. 10, No. 4 (2022)
       
  • Machines, Vol. 10, Pages 281: Rapid Calculation and Optimization of
           Vibration and Noise of Permanent-Magnet Synchronous Motors for EVs Based
           on Equivalent Structural Network

    • Authors: Tengfei Song, Huijuan Liu, Binbin Bu, Zhenyang Zhang
      First page: 281
      Abstract: Optimizing electromagnetic performance and vibration noise performance simultaneously is important when designing the drive motor for electric vehicles (EVs). This has not been fully explored, and there are only a few relevant studies. To achieve simultaneous optimization, this paper proposes an equivalent structural network (ESN) of stator assembly to calculate the modal distribution and harmonic response transfer functions. Based on the ESN model, the motor’s electromagnetic vibration noise harmonic response, such as acceleration and equivalent radiated power level (ERPL), can be quickly calculated. The feasibility of the established ESN model is verified by structural-field finite-element method (FEM) and modal hammer tests. Based on the modern optimization algorithm and the ESN model, an improved multi-physics and multi-objective optimization design approach is proposed for an optimized design of a 30kW interior permanent-magnet synchronous machine (IPMSM). The motor’s maximum output torque and ERPL were selected as optimization objectives, and then the ERPL and acceleration were recalculated using structural-field FEM to validate the accuracy of the optimal design. Finally, vibration acceleration tests were carried out on a manufactured prototype motor to verify the feasibility and validity of the proposed optimization design method.
      Citation: Machines
      PubDate: 2022-04-16
      DOI: 10.3390/machines10040281
      Issue No: Vol. 10, No. 4 (2022)
       
  • Machines, Vol. 10, Pages 282: A Lightweight Model for Bearing Fault
           Diagnosis Based on Gramian Angular Field and Coordinate Attention

    • Authors: Jialiang Cui, Qianwen Zhong, Shubin Zheng, Lele Peng, Jing Wen
      First page: 282
      Abstract: The key to ensuring rotating machinery’s safe and reliable operation is efficient and accurate faults diagnosis. Intelligent fault diagnosis technology based on deep learning (DL) has gained increasing attention. A critical challenge is how to embed the characteristics of time series into DL to obtain stable features that correlate with equipment conditions. This study proposes a lightweight rolling bearing fault diagnosis method based on Gramian angular field (GAF) and coordinated attention (CA) to improve rolling bearing recognition performance and diagnosis efficiency. Firstly, the time domain signal is encoded into GAF images after downsampling and segmentation. This method retains the temporal relation of the time series and provides valuable features for DL. Secondly, a lightweight convolution neural network (CNN) model is constructed through depthwise separable convolution, inverse residual block, and linear bottleneck layer to learn advanced features. After that, CA is employed to capture the long-range dependencies and identify the precise position information of the GAF images with nearly no additional computational overhead. The proposed method is tested and evaluated by CWRU bearing dataset and experimental dataset. The results demonstrate that the CNN based on GAF and CA (GAF-CA-CNN) model can effectively reduce the calculation overhead of the model and achieve high diagnostic accuracy.
      Citation: Machines
      PubDate: 2022-04-17
      DOI: 10.3390/machines10040282
      Issue No: Vol. 10, No. 4 (2022)
       
  • Machines, Vol. 10, Pages 283: Process Optimization of Robotic Polishing
           for Mold Steel Based on Response Surface Method

    • Authors: Yinhui Xie, Guangsheng Chang, Jinxing Yang, Mingyang Zhao, Jun Li
      First page: 283
      Abstract: Aimed to reduce surface roughness (Ra) and improve surface quality of mold steel, the optimizations of process parameters for robotic polishing, such as polishing pressure, feed speed and rotating speed of tool, are accomplish in this research. The optimum range of each parameter is obtained according to a single factor experiment, and the central composite design experiments on the three polishing parameters are conducted to establish a prediction model of surface roughness. Furthermore, a significance test of the prediction model is carried out through variance analysis. The optimum polishing parameters are obtained based on the analysis of response surface, and are then adopted in the polishing experiments of mold steel for validation. The experiment result of model verification indicates that the relative errors of predicted Ra ratio and actual Ra ratio are within the allowable range (maximum is 13.47%). It proves the accuracy of the roughness prediction model. Meanwhile, the experimental results of multipath polishing show that the surface roughness decreased effectively after polishing with the optimum polishing parameters. The prediction model of surface roughness and optimum polishing parameters are helpful to improve surface quality in robotic polishing for mold steel.
      Citation: Machines
      PubDate: 2022-04-18
      DOI: 10.3390/machines10040283
      Issue No: Vol. 10, No. 4 (2022)
       
  • Machines, Vol. 10, Pages 284: A Saturation-Based Method for Primary
           Resonance Control of Flexible Manipulator

    • Authors: Ruihai Geng, Yushu Bian, Liang Zhang, Yizhu Guo
      First page: 284
      Abstract: When primary resonance occurs, even a small external disturbance can abruptly excite large amplitude vibration and deteriorate the working performance of a flexible manipulator. Most active control methods are effective for non-resonant vibration but not for primary resonance. In view of this, this paper puts forward a new nonlinear saturation-based control method to suppress the primary resonance of a flexible manipulator considering complicated rigid-flexible coupling and modal coupling. A vibration absorber with variable stiffness/damping is designed to establish an energy exchange channel for saturation. A novel idea of modal coupling enhancement is suggested to improve saturation performance by strengthening the coupling relationship between the mode of the vibration absorber and the controlled mode of the flexible manipulator. Through stability analysis on the primary resonance response of the flexible manipulator with the vibration absorber, the saturation mechanism is successfully established and the effectiveness of the saturation control algorithm is validated. On this basis, several important indexes are extracted and employed to optimize saturation control. Finally, a series of virtual prototyping simulations and experiments are conducted to verify the feasibility of the suggested saturation-based control method. This research will contribute to the primary resonance suppression of a flexible manipulator under a complex external excitation environment.
      Citation: Machines
      PubDate: 2022-04-18
      DOI: 10.3390/machines10040284
      Issue No: Vol. 10, No. 4 (2022)
       
  • Machines, Vol. 10, Pages 285: RTSDM: A Real-Time Semantic Dense Mapping
           System for UAVs

    • Authors: Zhiteng Li, Jiannan Zhao, Xiang Zhou, Shengxian Wei, Pei Li, Feng Shuang
      First page: 285
      Abstract: Intelligent drones or flying robots play a significant role in serving our society in applications such as rescue, inspection, agriculture, etc. Understanding the scene of the surroundings is an essential capability for further autonomous tasks. Intuitively, knowing the self-location of the UAV and creating a semantic 3D map is significant for fully autonomous tasks. However, integrating simultaneous localization, 3D reconstruction, and semantic segmentation together is a huge challenge for power-limited systems such as UAVs. To address this, we propose a real-time semantic mapping system that can help a power-limited UAV system to understand its location and surroundings. The proposed approach includes a modified visual SLAM with the direct method to accelerate the computationally intensive feature matching process and a real-time semantic segmentation module at the back end. The semantic module runs a lightweight network, BiSeNetV2, and performs segmentation only at key frames from the front-end SLAM task. Considering fast navigation and the on-board memory resources, we provide a real-time dense-map-building module to generate an OctoMap with the segmented semantic map. The proposed system is verified in real-time experiments on a UAV platform with a Jetson TX2 as the computation unit. A frame rate of around 12 Hz, with a semantic segmentation accuracy of around 89% demonstrates that our proposed system is computationally efficient while providing sufficient information for fully autonomous tasks such as rescue, inspection, etc.
      Citation: Machines
      PubDate: 2022-04-18
      DOI: 10.3390/machines10040285
      Issue No: Vol. 10, No. 4 (2022)
       
 
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