Authors:Timothy Scott Co Chu, Von Eric Abag Damirez, Luzviminda Juanitez Ramos, Hedrick Justalero Sipacio, Leonardo Apresto Venancio, Alvin Yu Chua Abstract: Fused Deposition Modelling (FDM) is one of the widely utilized technology of low-cost 3D Printing. It uses plastic filament as material for Additive Manufacturing. To lessen the amount of filament consumption of prints, modification of the infill patterns was conducted. This study focuses on the introduction of new infill pattern – the lattice infill to increase material efficiency of 3D prints, compared to conventional infill patterns. Benchmark designs such as grid and cubic infill pattern were first created by the 3D printer slicing software. The proposed lattice infill design was created using a CAD software and rendered as STL file for compatibility with the slicing software. The three infill patterns were simulated in the slicing software to measure approximate product weight and the proposed design is simulated in an engineering simulation software to determine the stress performance and displacement when an external force is introduced. Results showed that the new infill pattern saves material up to 61.3% compared to conventional infill patterns. In effect, it increased the amount of prints produced per spool by 2.5 times. It is also found out that the lattice infill pattern print can resist to up to 1.6kN of compressive load prior to breaking. PubDate: 2020-06-01 Issue No:Vol. 10 (2020)
Authors:ASHA BHARATHI SHANKARATHOTA, RAVI KUMAR M S Abstract: Crack detection has always been a dominant requirement for steel industries to ensure quality production and seamless infrastructure maintenance. However, application complexities and defect morphological differences make existing approaches confined. Steel-strip surface often undergoes scratch, crack and fatigue conditions during production. Manual crack detection schemes are no longer effective in current day complex environment. Amongst major steel strip crack detection approaches vision based techniques have found potential; Filamentous crack which is caused due to fatigue or strain is fine-grained and thin and hence highly difficult to be detected by classical morphology and static threshold based schemes. In the present work steel strip surface (filamentous) crack detection system is developed which employs Varying-Morphological Segmentation (VMS) also called Neuron-Model Segmentation (NMS) in conjunction with local directive filtering and active contour propagation. The proposed method can be stated as an augmented vibrational framework that employs multi-directional filters for local crack-region identification followed by automated multi-directional region growing and iterative contour evolution which performs level set energy minimization to achieve accurate crack detection even under topological non-linearity and varying illumination conditions Simulation results with standard benchmark data has confirmed that the proposed method exhibits satisfactory performance for steel strip surface cracks. PubDate: 2020-06-01 Issue No:Vol. 10 (2020)
Authors:kaoutar lahmadi Abstract: This work presents the generalized Kalman Yakubovich-Popuv (gKYP) combined with the Takagi Sugeno (T-S) fuzzy model to design a fuzzy robust state feedback controller and a fuzzy robust observer-based in finite frequency (FF) domain. T-S fuzzy model is well known for its efficiency to control complex nonlinear systems. However, for wind generator system, the unknown parts are large and produce disturbances parameters. In order to attenuate, the level of the disturbances parameters observer based is utilized to estimate the unknown parts of the wind system. The control design method is based on Lyapunov function, the generalized gKYP with projection lemma, a PDC (Parallel Distributed Compensation) structure and the finite frequency (FF) technique. The proposed approach is formulated linear matrix inequalities (LMIs) to prove the asymptotic stability in (FF) domain. Finally, an example of wind turbine is show the validity of the proposed new approach. PubDate: 2020-06-01 Issue No:Vol. 10 (2020)
Authors:Ayman Abboudi, Fouad BELMAJDOUB Abstract: This paper gives a new approach of fault detection and isolation of hybrid dynamical systems based on hybrid observers and hybrid automata; a methodology for the design of dynamical observers has been proposed. The hybrid observer composed of two blocks: a location observer that identifies the current mode and a continuous observer that detects faults. Although this approach is interesting, it is still unable to detect instantly the change of the continuous state; as a result and in case of a fault, the system can't identify correctly the defected mode. In this paper, a new version is proposed to improve this approach and reach good diagnosis results. PubDate: 2020-06-01 Issue No:Vol. 10 (2020)
Authors:GINO IANNACE, Giuseppe Ciaburro, Amelia Trematerra Abstract: Wind has always represented a source of energy for human being. Currently, companies all over the world invest huge capital to build wind farms with the aim of obtaining the maximum possible economic return. Therefore, the identification of sites with the greatest windiness is necessary. These sites often reside in rural areas where the environmental impact of wind turbines, especially the noise impact, is significant. In this study, measurements of the noise emitted by several wind turbines located in South Italy were made. A selected range of the average spectral levels in a 1/3 octave band was used to identify the wind turbine operating conditions. A model based on neural network for detection operating conditions of the wind turbines was hence developed and applied. The results show the high accuracy of the forecast and identification model and suggest the adoption of this tool for several other applications. PubDate: 2020-06-01 Issue No:Vol. 10 (2020)
Authors:SUJITA JIWANGKURA, Peraphon Sophatsathit, Achara Chandrachai Abstract: Industrial Internet of Things (IIoT) is changing the future world and making a big impact on every company. SMEs are too small to have their own R&D. They may be left behind from the digital disruption age. Academic researches that describe the IIoT implementation strategies with Human Computer Interaction (HCI) for SMEs and adoption items of the strategies are rarely known. The paper reveals the IIoT implementation strategies with new HCI for SMEs in multi-dimensional facets. Analyses of IIoT implementation drivers, strategies, capabilities, and benefits on 30 articles from leading publishers such as Elsevier and Springer in the last 7 years are compared. Furthermore, the adoption items of IIoT implementation strategies are developed and quantitatively analyzed from 325 respondents of leading industries in Thailand manufacturing sector based on Technology, Organization, and Environment (TOE) adoption framework. The findings show that the 4 significant adoption items are lightweight flexibility, non-monotonous task of new HCI, top management’s real-time decision making, and market opportunity. These results permit better understanding of how SMEs can learn from the analyzed IIoT implementation strategies with HCI and the analyzed significant adoption items in order to adopt IIoT for their business empowerment, thereby maximizing the IIoT value. PubDate: 2020-06-01 Issue No:Vol. 10 (2020)
Authors:Bhaskar K.B., Paramasivam Alagumariappan, Mohamed Shuaib Y Abstract: This paper presents a flicker free operation of light emitting diode (LED) driver with Zeta converter for low power applications. In this work, the power factor of the LED driver is achieved by Zeta converter and it is operated in Continuous Conduction Mode (CCM). Further, the Zeta converter provides continuous current for an output system. Further, the design and simulation of the proposed circuit is done using MATLAB/Simulink software. Results demonstrate that the closed loop control system using fuzzy logic controller for the proposed LED driver provides good voltage regulation. Also, the proposed design and operations have been practically verified with a 40W LED driver module. PubDate: 2020-06-01 Issue No:Vol. 10 (2020)
Authors:Ahmed Jabbar Abid, Fawzi M. Al-Naima Abstract: Testing and evaluation of the photovoltaic array are important matters for researchers and students in the renewable engineering field. The collected data from the PV power plant gives a clear vision for the power plant production, array efficiency and fault detection. The presented system offers an electronic load connected to the PV array which is slightly increased from zero to the maximum designated value. It displays and stores all the voltage, current, and power measurements. It also calculates the voltage and current at the maximum power point, and the fill factor. All the measured data are documented within an Excel file on the computer; curves are plotted automatically to give the user a complete vision for the array behavior, power faults and the mismatching of the PV modules can be easily detected from these curves. The presented system describes all the electronic circuit schematics, how to select the appropriate electronic components with the proper rated values and offers a low-cost design that can be implemented with ease. PubDate: 2020-06-01 Issue No:Vol. 10 (2020)
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