Subjects -> INSTRUMENTS (Total: 63 journals)
Showing 1 - 16 of 16 Journals sorted alphabetically
Applied Mechanics Reviews     Full-text available via subscription   (Followers: 27)
Computational Visual Media     Open Access   (Followers: 5)
Devices and Methods of Measurements     Open Access  
Documenta & Instrumenta - Documenta et Instrumenta     Open Access  
EPJ Techniques and Instrumentation     Open Access  
European Journal of Remote Sensing     Open Access   (Followers: 18)
Experimental Astronomy     Hybrid Journal   (Followers: 38)
Flow Measurement and Instrumentation     Hybrid Journal   (Followers: 15)
Geoscientific Instrumentation, Methods and Data Systems     Open Access   (Followers: 2)
Geoscientific Instrumentation, Methods and Data Systems Discussions     Open Access   (Followers: 1)
IEEE Journal on Miniaturization for Air and Space Systems     Hybrid Journal   (Followers: 2)
IEEE Sensors Journal     Hybrid Journal   (Followers: 107)
IEEE Sensors Letters     Hybrid Journal   (Followers: 4)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Imaging & Microscopy     Hybrid Journal   (Followers: 7)
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan     Open Access  
Instrumentation Science & Technology     Hybrid Journal   (Followers: 7)
Instruments and Experimental Techniques     Hybrid Journal   (Followers: 1)
International Journal of Applied Mechanics     Hybrid Journal   (Followers: 8)
International Journal of Instrumentation Science     Open Access   (Followers: 41)
International Journal of Measurement Technologies and Instrumentation Engineering     Full-text available via subscription   (Followers: 1)
International Journal of Metrology and Quality Engineering     Full-text available via subscription   (Followers: 6)
International Journal of Remote Sensing     Hybrid Journal   (Followers: 144)
International Journal of Remote Sensing Applications     Open Access   (Followers: 49)
International Journal of Sensor Networks     Hybrid Journal   (Followers: 2)
International Journal of Testing     Hybrid Journal   (Followers: 1)
Invention Disclosure     Open Access   (Followers: 1)
Journal of Astronomical Instrumentation     Open Access   (Followers: 3)
Journal of Instrumentation     Hybrid Journal   (Followers: 31)
Journal of Instrumentation Technology & Innovations     Full-text available via subscription   (Followers: 2)
Journal of Medical Devices     Full-text available via subscription   (Followers: 4)
Journal of Medical Signals and Sensors     Open Access   (Followers: 1)
Journal of Optical Technology     Full-text available via subscription   (Followers: 4)
Journal of Research of NIST     Open Access   (Followers: 1)
Journal of Sensors and Sensor Systems     Open Access   (Followers: 12)
Journal of Vacuum Science & Technology B     Hybrid Journal   (Followers: 1)
Jurnal Informatika Upgris     Open Access  
Measurement : Sensors     Open Access   (Followers: 5)
Measurement and Control     Open Access   (Followers: 36)
Measurement Instruments for the Social Sciences     Open Access  
Measurement Techniques     Hybrid Journal   (Followers: 3)
Medical Devices & Sensors     Hybrid Journal   (Followers: 1)
Metrology and Instruments / Метрологія та прилади     Open Access  
Metrology and Measurement Systems     Open Access   (Followers: 8)
Microscopy     Hybrid Journal   (Followers: 7)
Modern Instrumentation     Open Access   (Followers: 57)
Optoelectronics, Instrumentation and Data Processing     Hybrid Journal   (Followers: 4)
PFG : Journal of Photogrammetry, Remote Sensing and Geoinformation Science     Hybrid Journal   (Followers: 4)
Photogrammetric Engineering & Remote Sensing     Full-text available via subscription   (Followers: 32)
Remote Sensing     Open Access   (Followers: 57)
Remote Sensing Applications : Society and Environment     Full-text available via subscription   (Followers: 9)
Remote Sensing of Environment     Hybrid Journal   (Followers: 94)
Remote Sensing Science     Open Access   (Followers: 30)
Review of Scientific Instruments     Hybrid Journal   (Followers: 20)
Science of Remote Sensing     Open Access   (Followers: 7)
Sensors International     Open Access   (Followers: 3)
Solid State Nuclear Magnetic Resonance     Hybrid Journal   (Followers: 3)
Standards     Open Access  
Transactions of the Institute of Measurement and Control     Hybrid Journal   (Followers: 12)
Videoscopy     Full-text available via subscription   (Followers: 5)
Труды СПИИРАН     Open Access  
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IEEE Sensors Journal
Journal Prestige (SJR): 0.619
Citation Impact (citeScore): 3
Number of Followers: 107  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1530-437X
Published by IEEE Homepage  [228 journals]
  • IEEE Sensors Journal

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      Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • IEEE Sensors Council

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      Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Usage of IR Sensors in the HVAC Systems, Vehicle and Manufacturing
           Industries: A Review

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      Authors: Muhammad Adeel Altaf;Jongsik Ahn;Danish Khan;Min Young Kim;
      Pages: 9164 - 9176
      Abstract: The use of thermal sensors is increasing in response to dealing with the problems of the visible light spectrum. These sensors measure the temperature of the object and convert it to some readable output. There is a diverse range of temperature sensors, and different sensors are used for different purposes. The choice of the sensor depends on the cost of the sensor, resolution, and level of accuracy. For instance, an IR camera combined with the RGB sensor can produce better human activity recognition. However, increase the cost of the machine. For some applications, a high resolution is not required and a low-cost sensor can satisfy the need. In this survey, we discuss the employment of thermal sensors in HVAC systems, vehicle, and manufacturing industries as they are heavily used in these industries. We reported the types of available thermal sensors and the sensors commonly used in each industry. This is followed by a comprehensive review of the application-specific methods. In the end, we may say that the selection of the thermal sensor has much importance as well as the choice of the suitable algorithms according to the given conditions to avail the maximum accuracy in our results.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Recent Developments for the Detection of Escherichia Coli Biosensors Based
           on Nano-Objects—A Review

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      Authors: Yousra Benserhir;Anne-Claire Salaün;Florence Geneste;Laurent Pichon;Anne Jolivet-Gougeon;
      Pages: 9177 - 9188
      Abstract: Advances in nanotechnology have made it possible in recent years to develop strategies for rapid and sensitive detection of pathogenic bacteria using new nanomaterials and the development of electronic nano-sensors. The detection of bacteria still faces problems such as long analysis time and complexity of the process. An alternative method is the use of biosensors, which combines a biological recognition mechanism with a physical transduction technique. Thus, a number of methods and manufacturing technologies have been developed in order to achieve performance in sensitivity, detection limit, label-free detection or real-time analysis. This review aims to focus on the state of the art of biosensors for the recognition elements of Escherichia coli in label-free biosensors with a particular focus on the beneficial use of nanomaterials and nano-objects for detection. Among the recent related biosensors based on nano-objects for E. coli detection, the technologies and measurement techniques are detailed by comparing their performances detection in terms of concentration range and detection limit. Detection becomes more sensitive and more flexible using nanoparticles as markers, and real-time electrical detection methods are dominant in comparison with optical ones. The lowest detection limit can be achieved for sensors based on metal (gold or silver nanoparticles) with optical detection techniques in contrast with electrical detection methods using measurement conductance.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • State-of-the-Art Light to Digital Converter Circuits Applicable in
           Non-Invasive Health Monitoring Devices to Combat COVID-19 and Other
           Respiratory Illnesses: A Review

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      Authors: Umar Mohammad;M. Asfandyar Awan;Amine Bermak;Fang Tang;
      Pages: 9189 - 9197
      Abstract: In the past few years, a tremendous advancement in the outcome of biomedical circuits and systems has been reported. Unfortunately, at the time of the sudden outbreak of COVID-19, the electronic engineering researchers felt dearth on their side to combat the pandemic, as no such immediate cutting-edge solutions were ready to recognize the virus with some standard and smart electronic devices. Likely, in this paper, a detailed comparative and comprehensive study on circuit architectures of the biomedical devices is presented. Mostly, this study relates the industry standard circuit schemes applicable in non-invasive health monitoring to combat respiratory illnesses. The trending circuit architectural schemes casted-off to tapeout non-invasive health-care devices available in the past literature are meticulously and broadly discussed in this study. Further, the comprehensive comparison of the state of art of the device performance in terms of supply voltage, chip area, sensitivity, dynamic range, etc. is also shown in this paper. The inclusive design processes of the health monitoring devices from Lab to Industry is thoroughly discussed for the readers. The authors think, that this critical review summarising all the trending and most cited health-care devices in a single paper will alternately help the industrialists to adapt and modify the circuit architectures of the health monitoring devices more precisely and straightforwardly. Finally, the demand for health monitoring devices particularly responsible to detect respiratory illnesses, measuring blood pressure and heart-rate is growing widely in the market after the the incident of COVID-19 and other respiratory diseases.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Surface Electromyography as a Natural Human–Machine Interface: A
           Review

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      Authors: Mingde Zheng;Michael S. Crouch;Michael S. Eggleston;
      Pages: 9198 - 9214
      Abstract: Surface electromyography (sEMG) is a non-invasive method of measuring neuromuscular potentials generated when the brain instructs the body to perform both fine and coarse locomotion. This technique has seen extensive investigation over the last two decades, with significant advances in both the hardware and signal processing methods used to collect and analyze sEMG signals. While early work focused mainly on medical applications, there has been growing interest in utilizing sEMG as a sensing modality to enable next-generation, high-bandwidth, and natural human-machine interfaces. In the first part of this review, we briefly overview the human skeletomuscular physiology that gives rise to sEMG signals followed by a review of developments in sEMG acquisition hardware. Special attention is paid towards the fidelity of these devices as well as form factor, as recent advances have pushed the limits of user comfort and high-bandwidth acquisition. In the second half of the article, we explore work quantifying the information content of natural human gestures and then review the various signal processing and machine learning methods developed to extract information in sEMG signals. Finally, we discuss the future outlook in this field, highlighting the key gaps in current methods to enable seamless natural interactions between humans and machines.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Biomedical Perspective in Terahertz Nano-Communications—A Review

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      Authors: Xiao-Xia Yin;Alireza Baghai-Wadji;Yanchun Zhang;
      Pages: 9215 - 9227
      Abstract: Terahertz (THz)-band (0.1~10 THz) communications are celebrated to be a crucial enabling technology for sixth generation (6G) wireless systems that fulfil the stringent requirements of future healthcare scenarios. Broadband THz sources have drawn the attention of researchers by virtue of their prominent detectability and their noninvasive and non-ionization properties. More importantly, the most advanced wideband THz sources enable THz communication in vivo with many appealing properties, including potential link capacities (terabit-per-second), miniature transceivers, and high energy efficiency. Compared to conventional devices, nano-scale devices will be potentially pivotal in subsequent medical diagnostics and treatment technologies, by virtue of the non-ionizing property of THz light and its high sensitivity in conveniently reaching delicate body sites. Thereby, real-time, label-free detection methods are expected to perform a crucial effect in clinical practice; however, difficulties such as unknown biological safety still need to be overcome. With channel modeling progress of the THz frequencies, we have considered both the radiation of the medium and the molecular absorption from the transmitted signal, and envisoned the possibility to solve the challenges such as the spectrum scarcity and capacity limitation.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Value of Information in Wireless Sensor Network Applications and the IoT:
           A Review

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      Authors: Faiga Alawad;Frank Alexander Kraemer;
      Pages: 9228 - 9245
      Abstract: Value of Information (VoI) is a concept to assess the usefulness of information for a specific goal, and has in the last decade experienced a growing interest also for Wireless Sensor Network (WSN) applications and the Internet of Things (IoT). By making the value of information explicit in the form of VoI, WSN and IoT applications should be able to better assess which information to spend their constrained resources on. However, the definition of VoI is highly application-dependent, which has led to a fragmented understanding of VoI, and there is a lack of a comprehensive overview. In this structured review, we first categorize application use cases and examine what VoI is used for, and explore the different approaches to defining VoI. We then provide a well-structured and comprehensive discussion of the specific approaches used in the literature to determine VoI, together with examples of use cases. We categorize the different approaches to calculating VoI, describe their properties systematically and distinguish between observed VoI and expected VoI. We also discuss adaptive VoI approaches and point towards future directions within the field.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Miniaturized Optofluidic Glucose Monitoring System Based on Enzyme
           Colorimetry

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      Authors: Qingmei Xu;Chongwei Zou;Chengtao Sun;Xingguo Zhang;Haixia Yu;Dachao Li;
      Pages: 9246 - 9254
      Abstract: Continuous glucose monitoring is of great significance in the diagnosis and treatment of diabetes. In this paper, a miniaturized and automatic optofluidic system was designed for continuous glucose monitoring. Interstitial fluid (ISF) was first obtained by an ISF transdermal extracting chip. Then, the glucose concentration in the ISF was detected by enzyme colorimetry. For accurate detection of the glucose concentration, the volume of transdermally extracted ISF was measured, and the volumes of ISF and colorimetric reagent in the mixed sample were controlled and mixed uniformly. To test the precision and stability of the system, different concentrations of glucose solutions (30–200 mg/dL) were used to simulate ISF extracted from skin. The results revealed that the measured glucose concentration correlated well with the reference concentration (R2 = 0.9976). In addition, the system achieved high-precision measurement of a low glucose concentration (30 mg/dL) even as the ISF volume fluctuated widely (0.5– $2.5 ~mu text{L}$ ), and the average absolute error was only 1.27%. Therefore, the system realized high precision for automatic and continuous monitoring of glucose in microvolume ISF samples, which would be a promising tool for the continuous monitoring of blood glucose concentration.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Sleeping Heart Monitoring Using Hydrogel-Textile Capacitive ECG Electrodes

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      Authors: Baoliang Feng;Hua Wei;Binjun Shi;Dazheng Zhao;Sijia Ye;Gang Wu;Rong Wang;Guokun Zuo;Zhisheng Wu;Jing Chen;Changcheng Shi;
      Pages: 9255 - 9267
      Abstract: In the application on sleeping heart monitoring by using capacitive electrocardiogram (cECG), a raw cECG signal with high quality is usually difficult to be obtained due to the low coupling capacitance composed of human skin, pajamas, bed sheet and sensing electrodes. This is mainly caused by a low relative dielectric constant of bed sheet and pajamas. In order to overcome this challenge, this study proposed a cECG system containing hydrogel-textile electrode for sleeping heart monitoring. The hydrogel layer was applied in an array pattern onto conductive textile to become a sensitive electrode in order to increase the coupling capacitance and lower the equivalent impedance as well, which was helpful to improve the quality of raw cECG signals. The reference electrode was linked to the circuit of the signal acquisition circuit to decrease the common-mode noises. The system incorporates eight membrane pressure sensors to capture the body’s sleep postures and detect the cECG signals from different sleep postures. The experimental results on tests with three different human sleep postures showed that the signal-noise ratio of the proposed system was close to the wet-electrode based ECG system. The sleeping heart monitoring experiments were conducted involving eight subjects with no constraint conditions through a period of two hours, the R-wave of the cECG signal was analyzed using RR interval extraction algorithms and the heart rate (HR) was calculated. The results showed that all subjects’ HRs during sleep state falls into a normal range, indicating that no signs of tachycardia and bradycardia can be observed.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Electrochemical Metallization Process on Screen-Printed Electrode for
           Creatinine Monitoring Application

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      Authors: Muhammad Asif A. Khushaini;Nur Hidayah Azeman;Chin-Hoong Teh;Rusli Daik;Ahmad Ghadafi Ismail;Burhanuddin Yeop Majlis;Muhammad Mat Salleh;Wan Ahmad Hafiz Wan Md Adnan;Tg Hasnan Tg Abdul Aziz;Ahmad Ashrif A. Bakar;Ahmad Rifqi Md Zain;
      Pages: 9268 - 9275
      Abstract: The formation and dissolution of the conductive paths in an electrochemical metallization (ECM) system is greatly influenced by the mobility of metal ions in the electrolyte, which can be utilized for the sensor application. Here, we report a demonstration of the ECM on the commercially available screen-printed electrode (SPE) strip, which is then utilized for monitoring the concentration of creatinine in an aqueous mixture. Prior to that, the working electrode was modified by drop casting an organic pentamer, 1,4-bis[2-(5-thiophene-2-yl)-1-benzothiopene]-2,5-dioctyloxybenzene (BOBzBT2). The electrostatic interaction between the BOBzBT2 radical cations and the creatinine molecules causes the resistance change in the electrochemical cell, influencing the variation of the ECM-induced pinched hysteresis loop. Consequently, the changes were recorded and the calibration curve was obtained. Compared to the unmodified SPE, the BOBzBT2-modified SPE demonstrated good performance in monitoring the concentration of creatinine. The sensor demonstrated 60 s response time with a sensitivity of 8.18 A dL g−1 for a linear detection range of 0.7–1.1 mg/dL. The selectivity and reproducibility of the modified sensor was also demonstrated. The setup’s simple fabrication procedures could open the way for the development of an ECM-based SPE sensor for creatinine monitoring.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Highly Sensitive Detection of the Antidepressant Fluoxetine With an
           Extended Gate Field Effect Transistor

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      Authors: Shokoofeh Sheibani;Adrian M. Ionescu;Parviz Norouzi;
      Pages: 9276 - 9288
      Abstract: Fluoxetine (FL) is one of the selective serotonin reuptake inhibitors, which is used as an anti-depressant, as well as anti-panic drug. In this work, a sensor for label-free recognition of trace amounts of FL is introduced, which is based on an extended gate field-effect transistor (EGFET). This sensor enables the detection and accurate measurement of FL concentrations over wide dynamic range. The sensing part of the device is a Pt electrode covered by a sensitive polyvinyl chloride (PVC) membrane. The functionalized Pt electrode acting as an extended gate of the EGFET, is connected to the internal gate of a MOSFET transducer. The sensing element of the PVC membrane is the insoluble ion-pair of FL cation and tetraphenylborate anion. The sensor performance for detection of FL was characterized in different ionic strengths of the matrix solution. Then, the sensor capability to operate in physiological phosphate-buffered saline (PBS) was assessed, where the sensor indicated two linear dynamic ranges of its response, with different sensitivities in 10−11-10−5 M and 10−5-10−3 M ranges. Also the calculated detection limit for the sensor was $2.63times 10^{-12}$ M. Moreover, the selectivity of the sensor was examined and validated in the presence of Citalopram, which is another anti-depressant drug with a similar structure to FL. We proposed a comprehensive analytical mapping of current sensitivity in all working regimes of the EGFET, providing a guide to the design of optimized sensors in any integrated systems of interest. Finally, the sensor was successfully exploited to assay citalopram in its pharmaceutical formulation.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Micro-Probe Potentiometric pH Sensor for Detection of Amplification in the
           LAMP Assay for White Spot Syndrome Virus (WSSV) in Shrimps

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      Authors: Jeric M. Flores;Mary Beth B. Maningas;Fortunato B. Sevilla;
      Pages: 9289 - 9295
      Abstract: A novel application of pH sensors is in the detection of amplification in nucleic acid-based methods for diagnosis of organisms. The detection is based on the production of hydrogen ions during the amplification process. In this study, a micro-probe potentiometric sensor for pH was fabricated and applied in the reagentless detection of the White Spot Shrimp Virus (WSSV) through the loop-mediated isothermal amplification (LAMP) technique. The pH micro-probe contained a pencil graphite modified with polypyrrole nanotubes through galvanostatic electrodeposition in the presence of methyl orange (MO). Electropolymerization parameters and potentiometric measurements parameters were optimized to obtain maximum sensitivity. The probe was characterized using Field Emission–Scanning Electron Microscopy (FE-SEM) and Fourier Transform-Infrared (FT-IR) Spectroscopy. The sensor showed a sub-Nernstian response (−45.5 mV/pH) at pH range 2–8 and LOD of ${5.19}times {10}^{-{8}}$ M; with minimum hysteresis ( $Delta $ m = ± 1.27 mV/pH), and low potential drift (±1.00 mV, pH 8). The probe was used to measure the pH of the microliter-volume reaction mixture at the start and at the end of the LAMP assay for WSSV. The probe detected pH change ( $Delta $ pH = −0.675) that occurred during the LAMP assay. This behavior correlated well with the results of fluorescence detection of the LAMP assay kit using SYBR Safe® DNA gel stain. A high diagnostic sensitivity (93.8%) and specificity (100%) was observed. The fabricated potentiometric sensor showed promising re-ult in monitoring positive LAMP reaction through measurement of pH. This provides a method to diagnose shrimp samples with WSSV that is rapid, easy-to-operate, and cost-effective.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Novel Method for Soft Contact Sensing Based on Electrical Impedance
           Sensitivity Images

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      Authors: Junwei Li;Kok-Meng Lee;
      Pages: 9296 - 9305
      Abstract: This paper presents a distributed soft contact sensing method based on a sensitivity mapping function, which relates the change in measured voltages to that in the elastomer conductivity due to contact force acting on its surface. The sensitivity-image-based sensing system uses a small number of boundary electrodes with a multiplexer to create different electric-field patterns to generate a series of sensitivity images for machine learning, significantly reducing the number of training data typically obtained with single-point indentation measurements. The mapping function, which does not rely on the knowledge of the electric and conductivity fields during online sensing, can be trained with only a small amount of measured data in the order of the square of electrode number. The proposed method has been experimentally evaluated on two 16-electrode prototypes trained with 129 and 80 data for two typical applications, which are tactile perception on a flat surface and contact force measurement in a model knee joint, respectively. The former verifies the measurement accuracy of the contact position and force magnitude while the latter demonstrates the application of this method for measuring the internal joint forces between two curved surfaces.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Design of a Square MEMS Piezoelectric Accelerometer With a Wide Range of
           Applicability, a Low Transverse Sensitivity Ratio, and High Accuracy

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      Authors: Cheng-Ying Li;Yueh-Han Chen;Zhi-Yuan Wei;Yi-Chen Ho;Sheng-Yuan Chu;Cheng-Che Tsai;Cheng-Shong Hong;
      Pages: 9306 - 9312
      Abstract: In this study, we attempt to design a new square MEMS lead-free piezoelectric accelerometer that can be used simultaneously in a wider frequency range than has been available in the past and in low-G sensing environments with high accuracy and low transverse sensitivity. Low transverse sensitivity is an important factor for high-accuracy accelerometers. The device is designed through the use of a structural formula, and ANSYS software is used to simulate the vibration mode and resonance frequency of the device, after which the MEMS process is used to complete the fabrication of the devices. The performance of the proposed device indicated that the resonance frequency was 1740 Hz, with a simulation error of only 3.3%; the Z-axis sensitivity was 1.96 mV/g, and the transverse sensitivity ratio was 0.6%. To the best of the author’s knowledge, the transverse sensitivity obtained in the present work is the lowest compared to the published data and specifications for commercial devices. It was successfully applied to a low-frequency robotic arm and a high-frequency turbo pump, where the operational status of the devices was monitored in-situ with high accuracy.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Performance Study of MEMS Piezoresistive Pressure Sensors at Elevated
           Temperatures

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      Authors: Vinod Belwanshi;Sebin Philip;Anita Topkar;
      Pages: 9313 - 9320
      Abstract: Three types of piezoresistive pressure sensors were designed and fabricated using different process technologies incorporating standard diffused piezoresistors, and oxide isolated polysilicon or single crystal silicon piezoresistors. The performance of these sensors up to an elevated temperature of 200°C and pressure of 140 bar was investigated by measuring the variation of sensitivity, offset voltage and hysteresis. At room temperature, the diffused piezoresistor based pressure sensor demonstrated sensitivity of 0.147 mV/V/bar and it was observed to operate up to the maximum temperature of 100 °C. The oxide isolated single crystal silicon piezoresistor and polysilicon piezoresistor based pressure sensors showed sensitivities of 0.211 mV/V/bar and 0.308 mV/V/bar respectively at room temperatures. These sensors could be operated up to the measured temperature of 200 °C without any failure. All types of sensors showed decreased sensitivities with temperature. With respect to the sensitivity at room temperature, the sensor with diffused piezoresistors exhibited 13% decrease of sensitivity at 100 °C. For oxide isolated single crystal silicon or poly silicon piezoresistors, the decrease in the sensitivity at 200 °C was 19.5% and 9.0% respectively y. At elevated temperatures of 200 °C, the sensors with oxide isolated polysilicon piezoresistors demonstrated the best performance in terms of lowest decrease of sensitivity, and variation of offset voltage and hysteresis.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Low-Temperature-Sensitivity Resonant Pressure Microsensor Based on
           Eutectic Bonding

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      Authors: Jiahui Yao;Chao Cheng;Yulan Lu;Bo Xie;Jian Chen;Deyong Chen;Junbo Wang;Ting Chen;
      Pages: 9321 - 9328
      Abstract: This paper presented a temperature-insensitive resonant pressure microsensor where silicon based resonators anchored on a pressure-sensitive diaphragm were vacuum packaged by a silicon cap based on eutectic bonding. Incoming pressures deformed the pressure-sensitive diaphragm and built stresses around resonators for frequency modulation while under temperature challenges, deformations of silicon based resonators and the vacuum cap were consistent and thus no stresses were generated on resonators. The temperature-insensitive resonant pressure microsensor was analyzed in both theoretical analysis and numerical simulations with confirmed high pressure sensitivities and low temperature disturbances. The resonant pressure microsensor was then fabricated by key steps of photolithography, deep reactive ion etching, and eutectic bonding and characterized in both open-loop and close-loop testing systems. Characterization results showed that the quality factors of resonators were $sim 10000$ with pressure sensitivity of 82.98 Hz/kPa and temperature disturbance of −0.63 Hz/° (the lowest result among previously reported resonant pressure microsensors). In summary, the temperature-insensitive resonant pressure microsensor developed in this study exhibited a fitting accuracy better than 0.02% FS within the pressure range of 10 to 120 kPa and the temperature range of −45 to $85^{circ }text{C}$ .
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Sensitivity Enhancement of SAW Pressure Sensor Based on the Crystalline
           Direction

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      Authors: Maria Muzamil Memon;Shuliang Pan;Jiang Wan;Tao Wang;Bin Peng;Wanli Zhang;
      Pages: 9329 - 9335
      Abstract: This work presents the sensitivity enhancement of AlN based surface acoustic wave (SAW) pressure sensor fabricated on the Si (100) wafer. Based on the theoretical analysis, a novel concept is proposed to improve pressure sensitivity with crystalline direction. The effect of wave propagation along < 100> and < 110> crystalline direction on pressure sensitivity of the SAW sensor has been studied by the finite element method. The simulation results indicate that the Si (100) based SAW sensor oriented in < 110> direction shown to possess high sensitivity compared to < 100> direction. The increase in sensitivity along the < 110> direction is due to a larger $gamma $ (velocity sensitivity to strain coefficient) value that results in increased velocity and large frequency shift. Two SAW pressure sensors, PS $_{< 100>}$ and PS $_{< 110>}$ with wave propagation along < 100> and < 110> directions, respectively, have been fabricated on Si (100) wafer to verify the sensitivity enhancement concept. Both sensors have been tested for the pressure range from 0–2 MPa. The measured sensitivity for the PS $_{< 100>}$ and PS $_{< 110>}$ are obtained as 112.68 ppm/MPa and 203.83 ppm/MPa, respectively, Which is significantly improved -y 80%. Additionally, the repeatability and linearity of PS $_{< 110>}$ have been measured and the deviation of the measured pressure sensitivity curve from the best linear fit is very small. The obtained results show that the developed sensor design has sufficiently high sensitivity with linear response and can be used for high pressure sensing applications.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Performance Enhancement of Flexible and Self-Powered PVDF-ZnO Based
           Tactile Sensors

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      Authors: M. Arjun Hari;Subash Cherumannil Karumuthil;Soney Varghese;Lintu Rajan;
      Pages: 9336 - 9343
      Abstract: Flexible, self-powered, and intelligent tactile sensors are essential for accurate sensing in prosthetic devices. This paper explores piezoelectric polyvinylidene difluoride - zinc oxide (PVDF-ZnO) nanocomposite layer-based sandwich assembly as tactile sensor. ZnO nanoparticle addition as filler can overcome the challenges associated with PVDF-based tactile sensors. The effect of filler particle size on the enhancement of sensing performance of PVDF-ZnO-based tactile sensors is investigated. Structural, morphological, piezoelectric and thermal studies were performed on the PVDF-ZnO composite layers using SEM, EDS, DC-EFM and Raman Spectroscopy. A comparative investigation of the potential developed across the sensor samples with different filler particle sizes was performed for touch and bending actions. The obtained results showed a remarkable improvement in performance due to particle size reduction of the ZnO fillers. The nanocomposite sensor with less filler particle size generated more voltage on the same applied force. The experimental analysis demonstrates that the filler size reduction can improve the piezo-voltage response up to 123 mV/N for dynamic touch events. The self-powered sensor also has excellent potential in detecting finger bending action with a response of 29 mv/°. The results demonstrate the promising application of the polymer nanocomposite-based sensor in the prosthetic application.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Two-Dimensional Coupling-of-Modes Model for Surface Acoustic Wave Devices
           Considering Power Flow Angle

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      Authors: Ran You;Wenchang Hao;Jiuling Liu;Minghua Liu;Shitang He;
      Pages: 9344 - 9350
      Abstract: A new form of two-dimensional coupling-of-modes (2D-COM) equations considering power flow angle was proposed and verified experimentally. By adopting a wave vector relationship in elliptic approximation form, the parabolic 2D-COM equations were improved into an elliptic form which is applicable to the simulation of surface acoustic wave resonators considering power flow angle (PFA-SAWR). Combined the method with COMSOL PDE module, a complete simulation model for PFA-SAWR’s frequency response was established. Take the periodic grating structure on the AT-22° quartz substrate (PFA ≈5.4°) as an example, a case analysis was carried out based on this new simulation model. The accuracy of the model was confirmed by comparing the results of 3D FEM analysis. Then, in the experiment part, a PFA-SAWR on the AT-22° quartz substrate was fabricated and measured, the frequency responses obtained by simulation and experiments are in good agreement. Finally, a new resonator structure which can effectively suppress the transverse modes and improve the Q value of resonators was introduced. This new simulation model provides an effective technique for accurately analyzing and designing PFA-SAWRs.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Design and Analysis of Limited-Angle Wound Rotor Resolvers

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      Authors: Tayfun Gundogdu;Burak Ozdincer;
      Pages: 9351 - 9360
      Abstract: In this study, the comprehensive design and analysis of a limited-angle wound rotor resolver (LAWRR) with high precision are presented. The effect of two major design parameters, including stator and rotor number of turns combinations, as well as the transformation ratio, on angular position accuracy is investigated. To determine the optimal number of turn combinations of LAWRRs with concentric windings (CWs), a simple analytical method consisting of calculating the total harmonic distortion (THD) percentage of the winding distribution waveform is employed. The fundamental operating principle and parametric analyses are carried out using finite element analysis (FEA), which is then followed by verification of the analytical calculations and determination of the optimal number of turn combinations. Moreover, the cross-correlation effect of the signal (stator) and excitation (rotor) winding configurations has been considered. Time-averaged, peak to peak, and maximum position errors were calculated for accuracy analyses. Finally, a prototype is built and tested to validate the analytical and numerical analyses, as well as the main parameters and angular position error.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Modeling and Design of Resonant Magnetic Field Sensors in the Scheme of
           Differential Magnetostrictive Actuation With Compact Bias Magnetic Circuit
           

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      Authors: Leixiang Bian;Weimin Peng;Zijun Huang;Yu Shi;Zhihong Zhuang;Chaopeng Luo;
      Pages: 9361 - 9370
      Abstract: A type of differential resonant magnetic field sensor is developed by employing the composite elements of FeGa plates, piezoelectric quartz crystal double-ended tuning forks (DETFs) and bias permanent magnets. The model and analysis show that the differential design brings the benefits of doubled sensitivity, increased linearity and low temperature drift. Importantly, a small and compact magnetic circuit containing a pair of permanent magnets and dual FeGa plates ensures the generation of differential actuation, which not only reduces the leakage flux but also improve the field-sensitivity and resolution. The magnetic circuit model based on the “lumped parameters” method is established. As an important aid, the distribution of magnetic flux density along the longitudinal direction of the FeGa alloy is simulated by finite element analysis software. In order to avoid the prediction error caused by parameter errors, simulations in different conditions are carried out for comparative analysis. This method ensures the magnetic circuit provides qualified magnetic field. The experimental results show that the differential resonant magnetic field sensor with frequency readout has the characteristics of high sensitivity of 4.4 Hz/Oe, high resolution of ${< }3.04times 10^{-4}$ Oe, low temperature drift and excellent linear (non-linearity error of 1.3%FS) and low hysteresis (1.5%FS) over its measurement full scale (FS) of ±100Oe.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Helical Motion Wound-Rotor Resolver

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      Authors: F. Zare;Z. Nasiri-Gheidari;
      Pages: 9371 - 9377
      Abstract: In this paper an integrated core, high reliability, linear-rotational resolver with a simple slotless configuration is proposed. The moving part of the proposed resolver has only one helical winding. While, its stator needs at least two individual windings to be able to determine the linear and angular position in simultaneous linear and rotational, helical, motions. Three different configurations are proposed for the stator’s windings: (1) helical and horizontally skewed winding (2) helical and vertically skewed winding (3) horizontally and vertically skewed windings. The influence of the mentioned configurations is discussed in the terms of sensor’s accuracy in independent and simultaneous linear and rotational motions. Furthermore, a decoupling technique is proposed for the helical motion. All the studies are done using three-dimensional (3-D) time stepping finite element method (TSFEM).
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Frequency-Variation Sensors for Permittivity Measurements Based on
           Dumbbell-Shaped Defect Ground Structures (DB-DGS): Analytical Method and
           Sensitivity Analysis

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      Authors: Jonathan Muñoz-Enano;Paris Vélez;Marta Gil;Ferran Martín;
      Pages: 9378 - 9386
      Abstract: It is shown in this paper that a microstrip line loaded with a dumbbell-shaped defect ground structure (DB-DGS) is useful for complex permittivity measurements. The working principle of the sensor is the variation in the notch (resonance) frequency and depth caused by the material under test (MUT), when it is put in contact with the sensitive region of the device, i.e., the capacitive slot. It is demonstrated that the relative sensitivity of the sensor, defined as the variation of the resonance frequency of the DB-DGS with the dielectric constant of the MUT relative to the resonance frequency of the bare structure, does not depend on the geometry of the DB-DGS, provided the substrate is thick enough. The relative sensitivity, the key figure of merit, is dictated by the equivalent dielectric constant of the substrate, and it increases as the substrate permittivity decreases. Using the circuit model of the sensing structure, simple analytical expressions providing the dielectric constant and the loss tangent of the MUT are derived. Such analytical formulas depend on the notch frequency and depth of the sensor with and without MUT in contact with it, i.e., easily measurable quantities. The analysis carried out is corroborated through full-wave electromagnetic simulation and experiments.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Digit Recognition in Air-Writing Using Single Millimeter-Wave Band Radar
           System

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      Authors: Hyeonmin Lee;Yonghee Lee;Hanho Choi;Seongwook Lee;
      Pages: 9387 - 9396
      Abstract: In this paper, we propose an air-writing method in a millimeter-wave band radar system. In particular, a method for removing undesired detection results due to a hand movement is proposed. In our experiments, we use a frequency-modulated continuous wave (FMCW) radar system using 62 GHz as the center frequency and 3 GHz as the bandwidth, which has a range resolution of several centimeters. After installing the FMCW radar on the table, radar sensor data is acquired by having subjects write single-digit numbers (i.e., numbers 0 to 9) in the air. However, in the case of writing numbers 4 and 5, even unnecessary hand movements can be detected by the radar sensor. To identify the numbers in which such undesired detection results occur, the Hough transform is applied to the detection result in the horizontal direction. Then, using different features for each number in the Hough transform domain, undesired detection results due to the hand movement that interfere with number recognition is removed. Finally, we evaluate the digit recognition performance with a convolutional neural network-based classifier. When undesired detection results are removed by the proposed method, the numbers can be recognized with an average accuracy of 97%.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Split-Type FMICW-Based Guided Wave Radar With Multisegmental Probe for
           Liquid Level Measurement

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      Authors: Bo Zhao;Yuanhong Xu;Yueyi Zhang;Shaoxiang Shen;Chuanjun Tang;Xiaojun Liu;Guangyou Fang;
      Pages: 9397 - 9407
      Abstract: In this paper, a specially designed guided wave radar device for measuring the liquid level in the nuclear industry is proposed. A split-type design is introduced to adapt to a strong radiation environment. An L-band frequency modulated interrupted continuous wave (FMICW) radar is designed to ensure the signal-to-noise ratio of echo signal after long-distance signal transmission, which provides the isolation between transmitter and receiver of more than 60 dB using the gating technology. To overcome the shortcomings of limited installation and maintenance space, a novel coaxial waveguide probe with a multi-segmental structure is proposed and simulated. An adaptive signal processing algorithm is developed to remove false echoes and eliminate measurement fluctuations. A prototype of the proposed measurement system is fabricated and evaluated. Static and dynamic liquid level experiments are performed in an outdoor environment to assess performance and verify the effectiveness of the proposed radar. The results show that the standard deviation measurement error of the proposed radar is within 0.4 cm. The proposed system is expected to have a high potential for applications in liquid level measurement under complex conditions.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Acoustic Localization With an Optical Fiber Silicon Microphone System

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      Authors: Simon Lorenzo;Olav Solgaard;
      Pages: 9408 - 9416
      Abstract: We develop a wavelength-multiplexed system of optical fiber-based photonic-crystal microphones for acoustic source localization. Our microphones use $392 mu text{m}$ wide and 450 nm thick photonic-crystal silicon diaphragms that we fabricate on the wafer scale and mount to an optical fiber with a simplified groove-based alignment. Our microphones have a bandwidth of acoustic sensitivity from 150 Hz to 50 kHz and an average minimum detectable pressure of $2 mu Pa/ sqrt {Hz}$ on resonance. The consistency of our microphone fabrication and assembly allows us to interrogate the pressure-sensitive Fabry-Pérot cavities using wavelength-sliced channels from the spontaneous emission of a C-band optical amplifier. Using our compact wavelength-multiplexed sensor system composed of standard fiber-optic communications hardware, we can localize acoustic sources in the environment to within 5 cm by a time-difference of arrival method.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Fading Suppression for Distributed Acoustic Sensing Assisted With
           Dual-Laser System and Differential-Vector-Sum Algorithm

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      Authors: Hao Li;Tao Liu;Cunzheng Fan;Baoqiang Yan;Junfeng Chen;Tianye Huang;Zhijun Yan;Qizhen Sun;
      Pages: 9417 - 9425
      Abstract: The sensing performance is severely affected by the intensity fading in the phase-sensitive optical time domain reflectometry ( $varphi $ -OTDR) based distributed acoustic sensing (DAS) system. The intensity fading manifests a stochastic amplitude fluctuation in the scattering signal. To suppress the fading noise, a heterodyne $varphi $ -OTDR system assisted with dual lasers with independent frequency, polarization, and initial phase is established to generate two pulses responses with different fading components at the same time. The backscattering signals from two individual probe pulses present different fading positions but possess the same phase change rate which is induced by the external disturbance. Through the differential-vector-sum algorithm including vectorization and phase differential, two complex Rayleigh backscattering beat signals from the two laser probes are efficiently synthesized, to simultaneously suppress the fading phenomenon caused by the inner pulse interference, polarization mismatch and phase mismatch. In the experimental validation, the probability of the fading channels in dual-laser scheme was significantly reduced from 9.4% to 1% compared with the single laser system, which is based on the resolution threshold of 2.1n $varepsilon / surd $ Hz at 10Hz. Moreover, the dual-laser scheme also proves the polarization insensitivity by inducing a rapid polarization perturbation for two probe lasers. Owing to the fading noise suppression, the dynamic signal’s SNR of the dual-laser system was improved more than 20dB in the intensity fading channels, while the temporal and spatial resolution were not deteriorated. The proposed fading suppressed distributed sensing system po-sesses the excellent performance, which makes it play an important role for practical distributed acoustic sensing.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • In-Fiber Integrated Quasi-Distributed Temperature Sensor Array With High
           Spatial Resolution for Silicon Nitride Igniter

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      Authors: Wenchao Li;Jiaxin Liu;Shuaichen Li;Quan Chai;Ye Tian;Xuelan He;Xianbin Wang;Yonggui Yuan;Jun Yang;Guoyong Jin;Jianzhong Zhang;Libo Yuan;
      Pages: 9426 - 9432
      Abstract: As a key component in the engine system, silicon nitride igniter’s stable and reliable operation is a necessary condition for the proper functioning of the engine system. However, an online high temperature sensor of silicon nitride igniter inside the engine is absent. This paper presents and demonstrates a novel in-fiber integrated high temperature sensor array with high spatial resolution for online temperature field measurement on a silicon nitride igniter. The sensor array with a series of weak reflectors is written by a femtosecond laser in the core of single-mode fiber. The reflectivity of each reflector can be controlled from 10−5~10−8 by adjusting the written power of femtosecond laser. Two adjacent weak reflectors form a compact fiber sensor. The size of a single sensor can be as small as 3–5 mm, so it is able to measure the temperature fluctuation in a space down to several millimeters. The five-sensor-array, with the help of a white light interference demodulation system, can measure high temperature up to 1000°C. Due to the advantages of high reliability, compact construction and simple fabrication, this high temperature sensor array can be widely applied in high temperature sensing applications with space constrains.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Nonlinearity Reduction in a Fiber Fabry-Perot Interferometer Interrogated
           by a Wavelength Scanning Optical Source

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      Authors: Rodolfo Martínez-Manuel;Jonathan Esquivel-Hernández;Sophie LaRochelle;
      Pages: 9433 - 9439
      Abstract: A novel method to reduce the nonlinearity effect of a wavelength scanning diode laser interrogating a low-reflectivity Fabry-Perot interferometer is presented. The interferometer is used for refractive index measurement. The proposed method allows improving the resolution of the system from $3times10$ −4 to $2times10$ −5; and generates a temperature insensitive sensing system. Using the resolution improvement and the temperature insensitivity, the proposed system was used to measure the thermo-optic coefficient of two liquid samples with well-known refractive index. To demonstrate the reliability of the proposed system, experimental results of the long-term performance of a six-month interval, using the same samples but different sensing heads, are presented. The proposed method allows the implementation of a standard four-pin diode laser as an optical source and a standard PIN photodetector for signal detection; permitting the implementation of a high-performance fiber sensor system based on small, light, and standard optoelectronic components. These characteristics are important for different applications such as medical and aerospace, for example, to monitor strain, curvature, pressure, and refractive index using fiber interferometers.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Model Test Study on Deformation Monitoring of 3D Printed Snowflake Shaped
           Pile

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      Authors: Lei Gao;Zhongquan Xu;Jiben Qian;
      Pages: 9440 - 9446
      Abstract: Snowflake shaped pile is a new type of special-shaped pile. In order to explore the deformation characteristics of the pile shaft under load, the model test of monitoring the deformation of 3D printed snowflake shaped pile is carried out. The strain information of 3D printed snowflake shaped pile under load is obtained, and the strain of pile shaft at different positions of snowflake shaped pile are analyzed in detail. The test results show that: Under the influence of boundary effect, there will be a coordinated deformation transition section of optical fiber strain near the pile head, which has a certain influence on the test results. If the influence of boundary effect is ignored, under the action of vertical load, the strain of 3D printed snowflake shaped pile decreases gradually with the increase of depth, and finally tends to 0 at the bottom of the pile. The strain of pile shaft at different positions of the same section is different. The strain of pile shaft at the junction of web and web is basically the same as that at the junction of web and flange. The pile shaft strain on the flange is larger, and the magnitude of strain difference at different parts will increase with the increase of load.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Optical Fiber Surface Plasmon Resonance Sensor Based on the Gold-Coated
           Hollow Fiber Structure for the Detection of Liquid With High Refractive
           Index

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      Authors: Yangyang Xu;Xian Zhang;Xiao-Song Zhu;Yi-Wei Shi;
      Pages: 9447 - 9453
      Abstract: A hollow fiber (HF) surface plasmon resonance (SPR) sensor based on the gold-coated HF structure for the detection of liquid with high refractive index has been presented experimentally for the first time. The designed sensors with different gold layer thicknesses are fabricated by the liquid phase deposition method. The performances of the fabricated sensors, including sensitivity and figure of merit, are analyzed with the measured transmission spectra. The experimental results show that the proposed sensor with a thicker gold layer exhibits the sensitivity and the corresponding figure of merit up to 8945 nm/RIU and 92 RIU−1, respectively, which is much higher than that of the silver-coated HF SPR sensor reported previously. Considering the extraordinary chemical stability and durability of gold, the presented sensor has large potential in biological and chemical applications. Moreover, the chemical method of coating smooth gold film in the hollow core of HF presented in this work is simple and cost-effective. It can be employed easily in the fabrication of other kinds of microstructured optical fiber devices coated with gold film and promote the experimental realization of them.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Highly Sensitive Curvature and Temperature Sensor Based on Double Groove
           Structure and Hollow Core Fiber

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      Authors: Xin Li;Jinjin Liang;Jinjian Li;Jingfu Ye;Yi Liu;Ming Chen;Zhenrong Zhang;Shiliang Qu;
      Pages: 9454 - 9461
      Abstract: In this paper, we propose a curvature and temperature sensor based on two symmetrical grooves and a hollow core fiber (HCF) filled with polydimethylsiloxane (PDMS). The two grooves are produced by splicing both ends of the polished HCF with two multimode fibers (MMFs). The proposed groove structure is sensitive to curvature, and the PDMS, with a high thermo-optical coefficient, makes the sensor highly sensitive to temperature. The experimental results show that the sensor exhibits a high sensitivity of −6.833 nm/m−1 in the curvature range of 0 m−1 to 45.97m−1, and a high sensitivity of 4.278 nm/°C in the temperature range of 25°C to 95°C. The proposed sensor can monitor curvature and temperature simultaneously in real-time, and has potential application prospects in industrial production, biomedicine, structural health monitoring, and other fields.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Toward a Wireless Wearable System for Bidirectional Human-Machine
           Interface With Gesture Recognition and Vibration Feedback

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      Authors: Yun Fang;Weichao Guo;Xinjun Sheng;
      Pages: 9462 - 9472
      Abstract: The research on bidirectional human-machine interface (BHMI) is of great significance, which can realize the interaction between human and machine. As the traditional Human-Machine Interface (HMI) device is limited by its wired connection and unidirectional functionality, this paper intends to develop a wireless wearable solution for BHMI with gesture recognition and vibration feedback. Compact design and wireless connection improve the flexibility and wearability of bidirectional interface node (BIN). By establishing a Distributed Wireless Sensor Network (DWSN), the proposed system allows up to 8 BINs to detect muscle activities simultaneously and control each Linear Resonant Actuator (LRA) independently. The data transmission throughput of the proposed system can be reduced by transmitting signal features instead of raw signals. With a sample rate of 2000 Hz and a resolution of 12 bits, BIN can achieve 94.48%±4.56% classification accuracy of six gestures. To evaluate the performance of the system’s bidirectional functionality, virtual control experiment was carried out. The experimental results show that the completion rate of the virtual control experiment reached 87% within 3.5s with vibration feedback. Overall, the outcomes of this study have great potential to promote the practical applications of bidirectional human-machine interaction, including rehabilitation therapy, fatigue prevention, virtual reality/augmented reality (VR/AR), and sensorimotor control of artificial devices.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Modified Model for the Temperature Effect-Induced Error in Hydrostatic
           Leveling Systems

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      Authors: Wu Qi;Xiao Xing;Zhao Kai;Chen Guoxing;
      Pages: 9473 - 9482
      Abstract: To investigate systematically how the temperature effect influences the measurement accuracy of a hydrostatic leveling system (HLS), ambient-temperature and temperature-gradient test platforms were built in the laboratory. The temperature of each measuring point of the HLS was collected by a high-precision temperature sensor, and the influences of the ambient temperature ${T}_{mathrm {A}}$ , temperature gradient ${T}_{mathrm {G}}$ , heating/cooling rate, communicating-pipe expansion coefficient, and measuring-point distance ${D}_{mathrm {test}}$ on the HLS measurement accuracy were analyzed quantitatively. The results show that the error of the two-HLS setup was caused by the expansion of the communicating pipe and the liquid between the datum point and the measuring point both under ambient-temperature and temperature-gradient conditions. The relative ambient-temperature influence coefficient $Delta {P}$ and temperature gradient influence coefficient $Delta {P}_{mathrm {t-G}}$ , respectively, had a linear correlation with the difference between the expansion coefficients of the communicating liquid and pipe ( $gamma _{mathrm {di}} - gamma _{mathrm {pi}}$ ). Moreover, $Delta {P}_{mathrm {t-A}}$ and $Delta {P}_{mathrm {t-G}}$ had a negative power relationship with ${D}_{mathrm {test}}$ for given communicating pi-e and liquid. A temperature-modified model was developed theoretically based on test results, and its reliability was verified via on-site tests.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Capacitive Mode Vapor Sensing Phenomenon in ZnO Homojunction: An Insight
           Through Space Charge Model and Electrical Equivalent Circuit

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      Authors: I. Sil;B. Chakraborty;K. Dutta;H. Awasthi;S. Goel;P. Bhattacharyya;
      Pages: 9483 - 9490
      Abstract: Conventionally employed resistive mode, vis-à-vis relatively non-conventional capacitive mode measurement technique for ZnO homojunction based alcohol vapor sensor is reported in this paper. ZnO homojunction comprising of sol-gel grown p-ZnO (sodium doped) nanoparticles and electrochemically derived undoped n-ZnO nanotubes was fabricated and after structural (FESEM) and electrical (I-V and C-V) characterizations, the sensing study (in both resistive and in capacitive mode) was carried out at room temperature (~25 °C). Compared to the DC resistance change based measurement, three distinctive features were noticed in capacitive mode sensing; (i) For methanol, the fabricated p-n homojunction device showed higher (~2415%) selectivity window (response magnitude difference with the nearest interfering species) in the capacitive mode, (ii) Capacitive measurement offered a dramatic improvement in the response magnitude (RM ~3021%) compared to its resistive counterpart (RM ~121%), (iii) Transient characteristics were sluggish in capacitive mode due to diffusion limited interactions. An innovative approach was adopted to understand the underlying sensing mechanism through correlation of an ambient dependent (in inert, in air and in vapor environment) space charge model of the homojunction device with the corresponding quantitative equivalent circuit.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Modeling and Analysis of SiC Capacitive Pressure Sensors Based on FEA
           Postprocessing With Infinitesimal Approach

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      Authors: Chengyi Liu;Jiangfeng Du;Limei Rong;Qi Yu;
      Pages: 9491 - 9499
      Abstract: In the design and reliability analysis of SiC capacitive pressure sensors (CPSs), the complex and harsh working environment causes irregular deformation of the sensors, which makes it difficult to analyze the capacitance. In addition, when finite element analysis (FEA) software is used for research, multi-physics coupling can be complicated, and different software adopts distinct capacitance analysis processes or even lacks related modules. Through applying the idea of the infinitesimal approach, this paper proposes a model of capacitance calculation for CPSs based on FEA postprocessing, including two mesh processing methods of reflection and densification. First, a SiC sensor is modeled and simulated under environmental stress by using Ansys Workbench. Afterward, the deformation results of the faces and edges of the insulating layers in the capacitor are exported. Then, MATLAB is used for processing the deformation data. Lastly, the capacitance value of the sensor is calculated in accordance with the concept of parallel plate capacitor. The research shows that within the pressure range of 0.5-100 kPa, the error of capacitance values between the proposed model and the theoretical calculation is less than 20%, which reduces to about 7% after the theoretical deviation is corrected; the error between the proposed model and the experiment of the fabricated SiC sensor is 4.7%, and that of capacitance ratio is 3.5%. This calculation model is validated to be suitable for all finite element software for analyzing the performance of different kinds of CPSs.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Robust Calibration of MEMS Accelerometers in the Presence of Outliers

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      Authors: Fethi Belkhouche;
      Pages: 9500 - 9508
      Abstract: MEMS accelerometers suffer from different problems such as random and systematic errors and the presence of outliers in the measurements. Proper calibration is necessary to obtain accurate results. Various methods exist but very few are designed for robust calibration. This paper explores methods for calibrating MEMS accelerometers in the presence of outliers. Optimization techniques based on Levenberg–Marquardt algorithm and linearization are used to solve the nonlinear calibration equations. Outlier detection methods such as RANSAC (random sample consensus), the Mahalanobis distance, and the median absolute deviation (MAD) are integrated within the optimization algorithm. Outlier scores are calculated and used to eliminate outliers or assign weights. The experimental results show that outlier detection and removal methods allow to achieve substantial improvement in the calibration process compared with non-robust methods. The median absolute deviation is the most effective in detecting outliers. In the presence of outliers, the average error for MAD and model-based method is 0.0136 (a.u.). For non-robust methods, the error is 3.82 (a.u.). For the Mahalanobis distance, the error is 1.8778 (a.u.). The results show that the calibration error is the smallest for the model—based method. The Mahalanobis distance presents higher calibration errors and is less capable of detecting outliers; however, it is still better than non-robust methods. Finally Levenberg–Marquardt algorithm presents slightly better results than linearization.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • On the Calibration of an Optical, High-Speed, Multiphase Microfluidic
           Sensor With Droplet Counting Applications in Lab-on-PCB Devices

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      Authors: Daniel H. Solano Teran;Matias Vázquez Piñón;Antonio Luque;Rubén R. López;Sergio Camacho-León;
      Pages: 9509 - 9520
      Abstract: The integration of microfluidics and droplet-based systems has led to platforms capable of characterizing multiple phases inside microchannels which can be an asset for many industries. Furthermore, recent developments on Lab-on-a-PCB devices focus to meet design specifications such as the ASSURED criteria (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable to end-users). However, most of these systems still present external equipment dependencies, complex setup and manufacturing processes, low reproducibility, along reduced information regarding calibration processes for ASSURED-based sensors. In this work, we developed a rapid and fully integrated calibration process for optical droplet-based Lab-on-PCB devices by means of an interfacial distance constant called $lambda $ , to obtain reliable and wide spectrum droplet detection and characterization results. To test the proposed calibration process, a low-cost optical droplet sensor was built using commonly available electronics components, consisting only of a fluid channel between a Light-Emitting Diode (LED) and a Light Dependent Resistor (LDR), which voltage variation is measured and processed with an Arduino Uno. After the proposed $lambda $ calibration of the platform, we were able to characterize different multiphase flow properties such as velocity, flow rate, droplet lengths, and volume for velocities up to 1000 droplets per second with the Mean Relative Errors (MRE) ranging from 2.4% up to 17%. The lowest MRE value was obtained using a two-phase flow system for flow from $20 mu text{L}$ /min up to $425 mu text{L}$ /min. In contrast- the highest MRE value we report was found for a three-phase flow system for droplets at $250 mu text{L}$ /min.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • An Ultra-Low-Power Read-Out Circuit for Interfacing Novel Gas Sensors
           Matrices

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      Authors: Rafael Puyol;Sylvain Pétré;Yann Danlée;Thomas Walewyns;Laurent A. Francis;Denis Flandre;
      Pages: 9521 - 9533
      Abstract: New gas sensing materials, like conductive polymers and nanomaterials-based composites, together with integrated circuit advancements have enabled a new paradigm in gas sensing where a matrix of different types of sensors is used to improve selectivity and sensitivity. In this paper we present a highly flexible read-out circuit for acquiring the dc resistance of the sensors in the matrix. It can measure values from 1 $text{k}Omega $ up to 33 $text{M}Omega $ , with a minimum SNR of 57 dB. It also offers a wide range of input configuration in terms of resistance and bias voltages to select the optimal bias point for each sensor and to accommodate a large range of sensor types. It achieves very low power consumption at a maximum current consumption of $194~mu text{A}$ and an energy per conversion ranging from 1.21 nJ up to 188 nJ thanks to the optimization of the frequency of operation. The circuit was fabricated in a 180 nm bulk CMOS process and a complete characterization of the circuit is presented including current consumption, signal-to-noise ratio, and transfer function. Finally, the circuit was tested in a real application for the measurement of NH3 and NO2 using two different types of sensors validating the design objectives and the capability of the read-out circuit for system-on-chip integrations.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Minimum Cauchy Kernel Loss Based Robust Cubature Kalman Filter and Its Low
           Complexity Cost Version With Application on INS/OD Integrated Navigation
           System

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      Authors: Qingwen Meng;Xuyou Li;
      Pages: 9534 - 9542
      Abstract: This article focuses on addressing the non-linear state estimations problem of measurement noise with non-Gaussian distribution, which is critical for the performance of the inertial navigation system (INS)/odometer (OD) integrated navigation system. Although many existing robust filters have been proposed to address the non-Gaussian issue, their performance is not quite ideal for non-Gaussian noise in real applications, such as impulsive and noises from multimodal distributions. Meanwhile, the computational complexity burden impedes the application of robust non-linear algorithms in INS/OD integrated navigation systems. This paper proposes a minimal Cauchy kernel Cubature Kalman filter (MCK-CKF) to address the non-Gaussian problem in general non-linear systems. In addition, a simplified MCK-CKF (SMCK-CKF) is proposed to reduce the computational cost in INS/OD integrated navigation system, meanwhile ensuring outstanding performance similar to MCK-CKF. First, we derive the MCK-CKF based on the new cost function, which is obtained by a combination of weighted least square (WLS) and MCK. Then, for the INS/OD integrated navigation non-linear system, which has a linear measurement equation, the SMCK-CKF is established by introducing the approximate method to calculate the matrix inversion in the combination of Kalman filter measurement updated and MCK-CKF framework. The computational complexity of the CKF/MCK-CKF/SMCK-CKF is analyzed and compared. The powerful robustness for tackling various forms of non-Gaussian interference of MCK-CKF is validated by simulation on a typical non-linearity system. Furthermore, the vehicle’s INS/OD integrated navigation experiment demonstrates that the MCK-CKF/SMCK-CKF have remarkable robustness, and the SMCK-CKF has outstanding time efficiency.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Fast and High-Performance Object Proposal Method for Vision Sensors:
           Application to Object Detection

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      Authors: Chao Jiang;Zhiling Wang;Huawei Liang;Shuhang Tan;
      Pages: 9543 - 9557
      Abstract: Use of the object proposal method as a preprocessing step for object detection of vision sensors has improved computational efficiency in recent years. Good object proposal methods require high object detection recall, low computational cost, good localization accuracy, and repeatability. However, existing methods cannot always achieve a good balance of performance. To solve this problem, we propose a fast and high-performance object proposal algorithm. First, we propose a construction method to enhance frequency features that are combined with a linear classifier to learn and generate a set of proposal boxes. Second, we propose a strategy of binarizing frequency features and classifiers to accelerate the calculation. Last, we propose a merging strategy to improve the localization quality of the proposal boxes. Empirically, for the VOC2007 and MSCOCO2017 datasets using the intersection over union (IOU) threshold of 0.5 and 104 proposals, our method achieves 99.3% object detection recall, 81.1% mean average best overlap, and 80% mean repeatability with an average time of 0.0014 seconds per image. The average time is three times faster than the current fastest method, and the mean repeatability is 11% higher than that of the region proposal network (RPN) method. We applied our method to the target detection of autonomous vehicles, and in the experiment with the Oxford RobotCar dataset, we achieved 95.6% detection precision and 91.2% detection recall. This work could provide a new way to improve real-time performance and detection accuracy in the object detection of visual sensors.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Simultaneous Calibration Method for Doppler Velocity Log Errors Based on a
           Genetic Algorithm

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      Authors: Jingxiao Liu;Haibing Li;Sile Ma;Jiangang Luo;Bibo Fu;Feng Zhang;
      Pages: 9558 - 9567
      Abstract: Doppler velocity log (DVL) errors affect the accuracy of strapdown inertial-navigation system (SINS)/DVL integrated navigation. Most existing calibration methods do not consider the problem of DVL sampling frequencies that are not fixed, and they cannot cope with large misalignment angles. This study proposes a method to calibrate internal and external DVL errors simultaneously, based on a genetic algorithm. To solve the problem of asynchronous SINS and DVL sampling, a method for unifying the time reference using cubic-spline interpolation is proposed. An error model for the DVL is established; the scale factor and misalignment angles are used as optimization genes for a genetic algorithm. The method can achieve high accuracy without requiring the misalignment angles to be small, significantly reducing the practical difficulty of installation. The results of simulation and shipboard experiments indicate that the calibration accuracy of the proposed algorithm is significantly better than that of the traditional method. For example, when the misalignment angle reaches 15°, the proposed algorithm has only a small error. If the carrier pitch angle changes to 5°, the root-mean-square error is reduced by 31.15% in the x-direction and 69.15% in the z-direction under highly dynamic conditions. The method thus seems likely to be useful in real-world engineering settings.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • COVID-19 Social Distance Proximity Estimation Using Machine Learning
           Analyses of Smartphone Sensor Data

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      Authors: Oleksandr Semenov;Emmanuel Agu;Kaveh Pahlavan;Zhuoran Su;
      Pages: 9568 - 9579
      Abstract: Airborne transmittable diseases such as COVID-19 spread from an infected to healthy person when they are in proximity to each other. Epidemiologists suggest that the risk of COVID-19 transmission increases when an infected person is within 6 feet from a healthy person and contact between them lasts longer than 15 minutes (also called Too Close For Too Long (TC4TL). In this paper, we systematically investigate Machine Learning (ML) methods to detect proximity by analyzing publicly available dataset gathered from smartphones’ built-in Bluetooth, accelerometer, and gyroscope sensors. We extract 20 statistical features from accelerometer and gyroscope sensors signals and 28 statistical features of Bluetooth signal, which are classified to determine whether subjects are closer than 6 feet as well as the subjects’ context. Using machine learning regression, we also estimate the range between the subjects. Among the 19 ML classification and regression methods that we explored, we found that ensemble (boosted and bagged trees) methods perform best with accelerometer and gyroscope data while regression trees ML algorithm performs best with the Bluetooth signal. We further explore sensor fusion methods and demonstrate that the combination of all three sensors achieves a higher accuracy of range estimation than when using each individual sensor. We show that proximity (< 6ft or not) can be classified with 72%-90% accuracy using the accelerometer, 78%-84% accuracy using gyroscope sensor, and with 76%-92% accuracy with the Bluetooth data. Our model outperforms the current state-of-the-art methods using neural networks and achieved a Normalized Decision Cost Function (nDCF) score of 0.34 with Bluetooth radio and 0.36 with sensor fusion.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Traction Resistance Estimation Based on Multi-Method Fusion for
           Distributed Drive Agricultural Vehicles

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      Authors: Chenyang Sun;Jun Zhou;Jianlei Zhao;
      Pages: 9580 - 9588
      Abstract: This study proposes a multi-method fusion algorithm to solve the problem of coupled traction resistance with the vehicle mass for distributed drive agricultural vehicles (DDAVs), because this coupling makes estimation measurements by agricultural vehicles difficult. Indeed, the proposed method decouples the vehicle mass and traction resistance. The vehicle mass was obtained using the recursive least square method and filtering the low-frequency parts of signals of driving force and longitudinal acceleration. After obtaining estimated vehicle mass, the dynamics method was coordinated and complemented with the kinematics method to observe the traction resistance. In the low-frequency load test, statistical performance criteria (SPCs) of the mass estimation were ${R} = 0.9985$ , root mean squared error (RMSE) = 0.0551 kg, and average of prediction accuracy (PA) = 98.02%. In addition, SPCs of the traction resistance estimation were ${R}=0.9655$ , RMSE = 23.0472 N, and average of PA = 99.28%. In the high-frequency load test, the maximum PA of the mass estimation reached 98.78%, and SPCs of the traction resistance estimation were ${R} = 0.9371$ , RMSE = 1266.3933 N, and average of PA = 85.62%. Experimental tests proved that the proposed method is robust and can accurately estimate the vehicle mass and traction resistance in real time.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Learning-Based Key Points Estimation Method for Burden Surface Profile
           Detection in Blast Furnace

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      Authors: Hong Wang;Wenbo Li;Tianxiang Zhang;Jiangyun Li;Xianzhong Chen;
      Pages: 9589 - 9597
      Abstract: Accurate Burden Surface Profile (BSP) detection is important for the operation of Blast Furnace (BF). The signal-to-noise ratio of radar signals changes greatly during both the charging period of BF and the long maintenance period of the radar device, which increases the difficulty of radar BSP detection. The traditional radar BSP detection method based on signal energy relies on manually selected detection thresholds according to the noise intensity. Hence, the accuracy of the traditional radar BSP detection method is not reliable in the long term. To address this problem, we propose a novel learning-based Key Points estimation (KP-BSP) method to detect the key points of radar reconstructed BSP image, and a new Key Points-based Connected Region Noise Reduction (KP-CRNR) algorithm to remove the noise-affected regions. The prediction deviation at detected key points (at the positions of the mechanical probes) is then used to correct the radar detection results, leading to the improvement of radar detection accuracy. The experimental data were collected from Wuhan Iron Steel Company No.7 BF. The results show that the proposed methods can achieve an average RMSE of 0.0156m, which is improved by more than 50% compared with previous methods. The long-term reliability of the proposed method is also demonstrated in this dataset.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Data Augmentation for Intelligent Mechanical Fault Diagnosis Based on
           Local Shared Multiple-Generator GAN

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      Authors: Qingwen Guo;Yibin Li;Yanjun Liu;Shengyao Gao;Yan Song;
      Pages: 9598 - 9609
      Abstract: Deep learning based intelligent fault detection for mechanical equipment has become an important research fields. However, due to various equipment and working conditions, it is difficult to collect sufficient fault samples by monitoring sensors, which restricts the accuracy of existing intelligent fault diagnostic approaches. In this paper, we propose a novel generative adversarial networks (GAN) based on local weights-shared multi-generator for the generation of fault data and building a fault diagnosis model. Unlike existing GAN based data augmentation methods, the proposed model contains multiple generators which are divided into several groups with each groups’ prior layers of generators weights-shared. By adversarial training, the discriminator gradually improves the performance of judging authenticity and fault categories with each group of generators acquiring the ability to generate a type of fault data. In this way, the proposed local shared multiple-generator GAN method effectively reduces mode collapse and generates more diverse fault data. The performance of the proposed method was validated on the fault datasets that are not applied in training stage. Compared with traditional deep learning diagnosis methods, the accuracy of fault diagnosis could be improved up to 30%, which indicates that the data generation model can generate diverse data and expand the fault data space.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Vision-Based Robot Grasping System

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      Authors: Hu Cheng;Yingying Wang;Max Q.-H. Meng;
      Pages: 9610 - 9620
      Abstract: Grasping is critical for intelligent robots to accomplish sophisticated tasks. Even with multimodal sensor fusion, accurately and reliably estimating grasp poses for complex-shaped objects remains a challenge. In this paper, we design a vision-based grasping platform for a more general case, that is, grasping a variety of objects by a simple parallel gripper with the grasp detection model consuming RGB sensing or depth sensing. Focusing on the grasp pose estimation part, we propose a deep grasp detector that uses a densely connected Feature Pyramid Network (FPN) feature extractor and multiple two-stage detection units to achieve dense grasp pose predictions. Specifically, for the feature extractor, the fusion of different layer feature maps can increase both the model’s capacity to detect the various size grasp areas and the accuracy of the regressed grasp positions. For each of the two-stage detection unit, the first stage generates horizontal candidate grasp areas, while the second stage refines them to predict the rotated grasp poses. We train and validate our grasp pose estimation algorithm on the Cornell Grasp Dataset and the Jacquard Dataset. The model achieves the detection accuracy of 93.3% and 89.6%, respectively. We further design real-world grasp experiments to verify the effectiveness of our vision-based robotic grasping system. The real scenario trials validate that the system is capable of grasping unseen objects, in particular, achieving robust and accurate grasp pose detection and gripper opening width measurement based on depth sensing only.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Scheduling of Multisensor for UAV Cluster Based on Harris Hawks
           Optimization With an Adaptive Golden Sine Search Mechanism

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      Authors: Jiahao Xie;Shucai Huang;Daozhi Wei;Zhaoyu Zhang;
      Pages: 9621 - 9635
      Abstract: Multisensor scheduling, a multi-objective optimization problem, simultaneously aims to find the optimal matching between sensors and targets in a certain period, that is, to generate the optimal multisensor scheduling scheme. Several sensor scheduling literatures proposed multisensor scheduling schemes incorporating various algorithms, but the majority of them dealt with sensors to targets in two dimensions. First, the visual relationship between sensors and UAV cluster targets is investigated, and a three-dimensional correspondence between sensors, targets, and time is designed while dividing the scheduling time. Secondly, the detection advantage of sensors to UAV cluster, sensor load, and sensor handover numbers in the scheduling time interval are summed to create multisensor scheduling objective functions for UAV cluster. Furthermore, for the UAV cluster optimization problem, a hybrid optimization algorithm is proposed, which integrates the golden sine mechanism and adaptive weight factor in Harris hawks optimization algorithm. Finally, extensive experimental and statistical analyses show that the models and algorithms proposed in this paper outperform the existing ones. It has better convergence, does not need additional computational cost, and generates better multisensor scheduling schemes.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • On-Line Algorithms of Stride-Parameter Estimation for in-Shoe
           Motion-Sensor System

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      Authors: Kenichiro Fukushi;Chenhui Huang;Zhenwei Wang;Hiroshi Kajitani;Fumiyuki Nihey;Kentaro Nakahara;
      Pages: 9636 - 9648
      Abstract: We propose two on-line algorithms for stride parameter estimation for an in-shoe motion-sensor system (IMS) system: one for on-line stride segmentation based on stable foot-flat detection using foot-sole angle and the other for a three-dimensional zero-velocity-update for accurate stride parameterization. We developed a small and lightweight IMS device, which consists of an inertial measurement unit, micro control unit, and peripheral electrical components, integrated with an insole so that it can be placed inside a shoe at the arch of the foot. Stride parameters, i.e., stride length, walking speed, foot height, circumduction, peak foot sole angle in the dorsiflexion and plantarflexion directions, and toe-in $/$ out angle, that characterize a user’s foot motion are estimated. We recruited 30 healthy participants and evaluated the precision of our IMS system by comparing the stride parameters calculated with this system with those acquired from a motion-capture system. The results indicate the precision of the system in terms of the root mean square error for stride length of 0.069 m, walking speed of 0.094 $text{m}/text{s}$ , foot height of 1.5 cm, circumduction of 1.0 cm, peak foot-sole angle in the dorsiflexion of 3.3 deg. and in the plantarflexion directions of 5.9 deg., and toe-in $/$ out angle of 2.5 deg. Our IMS system has good precision regarding all parameters and high reliability and promises to contribute to personal health and wellness services and solutions by serving as a powerful and practical tool for objective gait assessment in real-world contexts.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Cross-Domain Fault Diagnosis Based on Improved Multi-Scale Fuzzy Measure
           Entropy and Enhanced Joint Distribution Adaptation

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      Authors: Aisong Qin;Hanling Mao;Kuangchi Sun;Zhengfeng Huang;Xinxin Li;
      Pages: 9649 - 9664
      Abstract: For cross-domain fault diagnosis of rotating machinery, how to reduce the discrepancy between the source and target data distributions is still a key problem. To this end, this study proposes a novel cross-domain fault diagnosis method based on improved multi-scale fuzzy measure entropy and enhanced joint distribution adaptation, aiming to address inconsistent data distribution between the source and target domains. Specifically, improved multi-scale fuzzy measure entropies are firstly developed to generate discriminative and similar features from original vibration signals. Subsequently, through embedding maximum covariance discrepancy into the existing joint distribution adaptation, an enhanced joint distribution adaptation model is utilized to reduce the distribution discrepancy between two domains. As such, more discriminative and similar features are obtained in a new subspace. The unlabeled samples in the target domain are classified by a simple statistical classifier. Finally, three public and private datasets are used to verify the effectiveness and superiority of the proposed method. Experimental results demonstrate that improved multi-scale fuzzy measure entropies have better distinguishing ability and transferable ability than several existing entropy methods, and the enhanced joint distribution adaptation is more generalized to transfer scenarios with complex data distributions.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Dynamic Calibration of Triaxial Accelerometers With Simple Setup

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      Authors: Federico Pedersini;
      Pages: 9665 - 9674
      Abstract: In the dynamic techniques for calibration of triaxial accelerometers, the sensor is held in motion during data acquisition; the acquired time-varying acceleration is in general more informative than the constant acceleration acquired in static calibration approaches. Dynamic methods, however, typically require complex and expensive calibration setups based on high-precision moving benches, to guarantee accurate a-priori knowledge of the acceleration applied to the sensors under test. This article presents a dynamic calibration procedure working with a very simple and inexpensive setup: a tilted, freely-rotating bench, made of a simple wheel mounted on a static support. The accelerometer is fastened to the bench, which is then manually set into rotation; the acceleration signal is then acquired while the bench is freely rotating. No a-priori knowledge is required about the bench rotation: the proposed calibration procedure estimates both the calibration parameters and the bench motion. To keep the setup as simple as possible, an effort has been made to minimize also the necessity of prior knowledge of the bench geometry: only the distance of the sensor from the rotation axis needs to be known, which can be easily obtained through direct measurement on the bench. The proposed calibration has been tested both on synthetic data, to prove the absence of estimation biases and to evaluate the potential accuracy of the estimated parameters, and on real data from a MEMS triaxial accelerometer, to assess the practical usability and measure the actual precision of the procedure.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • An Improved Sliding Matched Filter Method for Interrupted Sampling
           Repeater Jamming Suppression Based on Jamming Reconstruction

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      Authors: Lu Lu;Meiguo Gao;
      Pages: 9675 - 9684
      Abstract: The development of the digital radio frequency memory (DRFM) has led to the interrupted sampling repeater jamming (ISRJ) becoming increasingly popular in electronic countermeasure (ECM). It is coherent with the emitted signal and extremely limits radar target detection which significantly obstructs radar electronic countercountermeasure (ECCM). In this paper, we study the ISRJ suppression for pseudo random code continuous wave (PRC-CW) radars. First, the relationship between the ISRJ and the radar waveform is obtained by analyzing the ISRJ principle. Second, the intermittent feature of the ISRJ with matched filter sliding is discussed and used to determine the retransmitted sampled slices (RSS). Third, the jamming signal is reconstructed using the minimum residual criterion and excluded from the echo signal. In the proposed method, we make the most of the information of the jamming signal for improving the anti-ISRJ performance in the low SNR regimes. This information pertains to the amplitude of the jamming signal being considerably higher than that of the real target signal. Fourth, utilizing this characteristic of the jamming signal, we propose an improved sliding matched filter method based on the RSS reconstruction. Last, numerical simulations illustrate the effectiveness of the proposed method and validation of the theoretical analysis.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Refraction Surface-Based Stellar Atmospheric Refraction Correction and
           Error Estimation for Terrestrial Star Tracker

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      Authors: Zhen Wang;Jie Jiang;
      Pages: 9685 - 9696
      Abstract: Stellar atmospheric refraction imaging error, as the optical imaging variation of starlight before and after passing through Earth’s atmosphere, is one of the key issues for terrestrial star trackers to obtain accurate attitude measurement results. To resolve the problem, a refraction surface-based stellar atmospheric refraction correction method is presented in this paper. Different from existing correction methods, a new atmospheric refraction feature, i.e., stellar atmospheric refraction surface, is proposed to represent the random irregular optical phenomena of starlight, and avoids the limitations of theoretical atmospheric models and empirical formulas. On the basis of the principles of “collinear refraction surfaces”, “invariable refraction surface”, the proposed model successfully realizes the accuracy atmospheric refraction correction by the sensor itself, without external atmospheric parameters. Then, by analyzing the error factors parallel and perpendicular to the atmospheric refraction surface, the atmospheric refraction correction error estimation model is established to forecast the attitude accuracy after correction. Numerical simulations and night sky experiments validate the reliability of our atmospheric refraction correction method and error estimation model. The average angular distance error of the test star tracker is reduced from $31.1310'$ into $1.7705'$ , which is significantly decreased by 94.31%.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Sub-Nyquist Sampling of ECG Signals With Differentiated VPW Optimization
           Model

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      Authors: Guoxing Huang;Zeming Yang;Weidang Lu;Hong Peng;Jingwen Wang;
      Pages: 9697 - 9712
      Abstract: In recent years, developments in wearable technologies and wireless communication have enabled wearable ECG monitoring. Long-term ECG monitoring result in large amounts of data. To sub-Nyquist sampling ECG signal, recently developed finite rate of innovation (FRI) technology is a practical option. However, existing FRI sampling schemes generally suffered from large model mismatch errors and insufficient reconstruction accuracy. In this paper, a sub-Nyquist sampling scheme based on the differentiated VPW optimization model is proposed for ECG signals sampling. The original ECG signal is modeled as a linear combination of several differentiated Variable Pulse Width (VPW) pulses and a model mismatch error signal. Then, a two-channel sampling framework is proposed to sample ECG signals with a sub-Nyquist rate. To improve the accuracy of the reconstruction, optimizing the reconstruction is considered. We formulate the objective function of the optimization to minimize the model mismatch error signal. A particle filter-based optimization method is proposed to solve the objective function with a high-dimensional variable. Block coordinate descent (BCD) technique is considered in the proposed optimization method. Finally, we conduct several simulations with real ECG signals from MIT-BIH Arrhythmia Database to test the performance of our proposed scheme. Simulation results have demonstrated the reconstruction accuracy of our proposed scheme outperforms other related schemes.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Gait-Based Person Identification and Intruder Detection Using Icm-Wave
           Sensing in Multi-Person Scenario

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      Authors: Zhongfei Ni;Binke Huang;
      Pages: 9713 - 9723
      Abstract: Using mm-wave sensing to identify persons by the way they walk has recently emerged as a promising solution of biometrics, and has found versatile applications in security surveillance, automatic access control, and health monitoring. In this paper, we build a system named MGait for indoor multi-person identification and intruder detection based on gait micro-Doppler (m-D) signatures captured by a low-cost mm-wave radar. In multi-person scenario where multiple subjects concurrently share and walk within the same physical space, the proposed system continuously detects and separately tracks each subject in the range-Doppler (R-D) space frame by frame to extract their respective gait m-D signatures. Then, an open-set identification network is trained by a large-margin Gaussian mixture (L-GM) loss to learn highly discriminative feature representations and compel the learned features of the training set to follow a Gaussian mixture distribution, with each component representing a registered user. As such, the known users can be directly identified based on the class-posterior probability and the intruder can also be rejected by setting a probability threshold. The proposed system is verified on real radar measurements collected by a 77 GHz FMCW radar, achieving an overall accuracy of 88.59% in identifying up to 5 subjects, including 1 known user and 4 intruders, freely and concurrently moving in a corridor space.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • NQRELoc: AP Selection via Nonuniform Quantization RSSI Entropy for Indoor
           Localization

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      Authors: Hualiang Li;Zhihong Qian;Guiqi Liu;Xue Wang;
      Pages: 9724 - 9732
      Abstract: Received signal strength indicator (RSSI) of WiFi access point (AP) is a primary sensor data used for indoor fingerprint localization. User sends its online RSSI to server to estimate its position by matching with RSSI fingerprints database which built in the offline phase. An important goal of indoor fingerprint localization is to increase the accuracy while reduce the storage cost. Meanwhile, APs perform different effects on target estimation and mapping metric in RSSI fingerprint localization. In this paper, a novel localization model based on the nonuniform quantization RSSI entropy (NQRELoc) is proposed to address these problems. First, to select the APs that contribute more to the localization, the nonuniform quantization RSSI entropy (NQRE) is introduced to quantify AP’s discernibility and select APs whose signals show sufficient differentiation to construct an offline fingerprints database. Then, the entropy-weighted euclidean distance (EWED) is used as a metric to measure the similarity of online RSSI vectors and offline RPs fingerprints. Finally, NQRELoc locates the target by the improved entropy-weighted K nearest neighbor (IEWKNN) algorithm, which takes the APs effect into target estimation. To validate the proposed algorithm, a large scale of experiments and simulations are implemented. The results demonstrate that NQRELoc can not only reduce the storage overhead but also improve the positioning accuracy compared to the other existing techniques.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Azure Kinect Calibration and Parameter Recommendation in Different
           Scenarios

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      Authors: Fan Wei;Guanghua Xu;Qingqiang Wu;Jiachen Kuang;Peiyuan Tian;Penglin Qin;Zejiang Li;
      Pages: 9733 - 9742
      Abstract: The series of Kinect, which has the third-generation device now, is a low-cost scene information collection sensor to capture the color information and depth information from the scene at the same time. Due to the hardware structure of the sensor, the color image and the depth image shot by Kinect is not homologous. In this article, we compared the hardware parameters of different Kinect three generations of products, and we have calibrated the RGB camera and IR (infrared) camera of Azure Kinect, so as to the internal parameters and external parameters between the RGB camera and IR camera, and align the color image and depth image taken with Azure Kinect. At the same time, we evaluated the shooting accuracy and stability of Azure Kinect’s depth camera, and conducted experiments on the relationship between shooting error and measurement distance on three generations of products, also the parameter optimization suggestions are provided. In addition, according to different usage scenarios, we recommend the shooting parameters and the image effective range of the sensor simultaneously.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Bayesian Method for ViSAR Image Fusion Using Effective Reflection
           Coefficient

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      Authors: Dan Song;Ratnasingham Tharmarasa;Kun Han;Wei Wang;Mike McDonald;Thiagalingam Kirubarajan;
      Pages: 9743 - 9753
      Abstract: Since the isotropic scattering assumption does not hold in a wide-angle synthetic aperture radar, the video synthetic aperture radar (ViSAR), a new sensing mode by sequentially forming SAR images on a series of contiguous or overlapping sub-apertures, has the promising capability to capture aspect-dependent scattering behavior of objects. In this paper, a new Bayesian method for fusing ViSAR images is proposed. First, the notion of effective reflection coefficient is defined to characterize aspect-dependent scattering behavior of objects. Based on the ViSAR images sequence, the spatial effective reflection coefficient in the area of interest (AOI) when observing at different aspect angles are estimated. A Bayesian hypothesis testing is then derived to fuse the obtained effective reflection coefficient estimates for detecting scatterers in the AOI. The performance of the proposed method is evaluated and compared with that of the conventional GLRT-based ViSAR image fusion method in a simulated scenario. Numerical results demonstrate the superiority of the proposed method in capturing the aspect-dependent scattering characteristics as well as the spatial structure of objects.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Stable Adaptive Adversarial Network With Exponential Adversarial
           Strategy for Bearing Fault Diagnosis

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      Authors: Jing Tian;Dong Wang;Liang Chen;Zhongkui Zhu;Changqing Shen;
      Pages: 9754 - 9762
      Abstract: Given an industry’s development, fault diagnosis has received significant attention. Owing to complex and changeable working conditions and lacking marked fault data for fault diagnosis, domain adaptation has become a new solution. However, a variable operating environment will cause changes in data distributions, which complicates domain adaptation. Resultantly, a challenge exists in measuring a data distribution and combining it with domain adaptation. Thus, this article proposes a method of dynamically adapting a marginal distribution and a conditional distribution, including a new adaptive factor, which can use distance metrics and exponential functions to stably adapt to different data distributions in source and target domains. By dynamically adjusting the importance of the marginal and conditional distributions in a model, the proposed model can achieve excellent diagnostic results. Compared with a fixed-scale model without an adaptive factor that only has high diagnostic results for some working conditions, the proposed model has stable and accurate diagnosis results, whether it is facing different speeds and different loads. In addition, experiments are conducted to verify the effectiveness and usability of the proposed model.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Novel SINS/USBL Tightly Integrated Navigation Strategy Based on Improved
           ANFIS

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      Authors: Shaohua Pan;Xiaosu Xu;Liang Zhang;Yiqing Yao;
      Pages: 9763 - 9777
      Abstract: Strapdown inertial navigation system (SINS)/ ultra- short baseline (USBL) integrated navigation system is widely used in navigation and positioning of underwater vehicle. In an unknown and complex underwater environment, unstable USBL measurement information can lead to decreased navigation accuracy. In the traditional method, the interference to USBL is uniformly modeled as outliers, but in practice, it is also represented as slowly varying errors, update irregular errors. The latter two errors are not easy to be detected at the beginning of occurrence. Therefore, a SINS/USBL integrated navigation technology based on novel adaptive neural fuzzy inference system (ANFIS) is proposed. This model can detect and compensate abnormal USBL information and maximize USBL information. In order to improve the prediction accuracy of ANFIS, an ANFIS algorithm based on variational Bayesian Kalman filter and principal component analysis (PCA) is proposed to avoid the decrease of positioning accuracy caused by false compensation. The simulation shows that the designed ANFIS algorithm can accurately predict the above anomalies. And it can overcome the problem that USBL measurement anomalies are difficult to be detected at the initial stage. Combined with the proposed integrated navigation technology, it obtain the same positioning accuracy in complex environment as in good environment. The effectiveness and robustness of the proposed method are verified by river experiment.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • An Ultra-Low-Power Strain Sensing Node for Long-Range Wireless Networks in
           Carbon Nanotube-Based Materials

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      Authors: A. Hernández-Benítez;A. Balam;J. Vázquez-Castillo;Johan J. Estrada-López;R. Quijano-Cetina;A. Bassam;F. Aviles;A. Castillo-Atoche;
      Pages: 9778 - 9786
      Abstract: The application of flexible electronics to device-engineering technologies has enabled the manufacture of low-cost, lightweight, extensible, and foldable sensors. However, despite the efficient response of composite materials for the detection of signal stimuli reported in the state-of-art literature, there is an area of opportunity for the implementation of ultra-low-power wireless sensor networks (WSN) with novel flexible materials in precision medicine, structural health monitoring, environmental sensing, wearables and applications based on the Internet of Things (IoT). This article proposes a portable strain sensing node based on multiwall carbon nanotubes (MWCNTs)/polypropylene(PP) composites for Long-Range (LoRa) wireless networks with IoT connectivity. The nanostructured sensor node with 4 wt% MWCNTs shows high piezoresistive sensitivity with gage factors of ~ 4.5. A system identification problem is conducted following a constrained optimization model, which estimates the sensor errors due to nonlinearity and system parameters, providing a stable strain response with high accuracy. An energy management strategy is also implemented for the efficient integration of a microcontroller unit in combination with a wireless LoRa communication transceiver, enabling the utilization of flexible composite materials into a wireless nanostructured sensing network with ultra-low-power consumption of 0.8705 mW. The experimental results of the MWCNT/PP strain sensing node show the feasibility for a variety of IoT-WSN applications.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Cognitive Radar Waveform Design and Prototype for Coexistence With
           Communications

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      Authors: Mohammad Alaee-Kerahroodi;Ehsan Raei;Sumit Kumar;Bhavani Shankar M. R. R.;
      Pages: 9787 - 9802
      Abstract: The need for cognitive radar systems that automatically adapt their transmit waveform and receive processing to the environment is growing along with the desire for integrating with communications. Indeed, the radio frequency spectrum will continue to become more crowded, and in this context, the new generation of radar systems will require to sense the frequency band and avoid making interference for other systems, like communications. In this paper, we present a spectrum-sharing prototype that demonstrates the application of waveform optimization for a scenario of coexistence between communications and cognitive radar systems. To this end, we define a bi-objective optimization problem for waveform design that provides both spectrum compatibility and small cross-correlation for the waveform set. The optimization problem is non-convex and NP-Hard, where we solve it iteratively using the Coordinate Descent (CD) framework. By sensing the environment in real-time and sequentially optimizing radar transmit waveform, the applicability of the proposed optimization algorithm is illustrated in a custom-built prototype, and its performance is validated and evaluated through SNR measurement for the radar system and throughput calculation for a realistic LTE downlink communication.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Surface-Plasmon-Resonance Based Narrow-Bandwidth Infrared Carbon Monoxide
           Detection System

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      Authors: Kuan-Chou Lin;Ming-Ru Tang;Ching-Fuh Lin;Si-Chen Lee;Chih-Ting Lin;
      Pages: 9803 - 9810
      Abstract: A narrow-bandwidth non-dispersive infrared (NDIR) carbon monoxide (CO) detection system is demonstrated in this work. Based on surface-plasmon-resonance devices, the newly developed CO detection system can be implemented without expensive optical filters. In this CO detection system, the narrow-bandwidth infrared thermal emitter (NBITE) has a Au $/$ SiO2 $/$ Au tri-layer structure with hexagonal-hole pattern on the top gold layer. The pattern is a waveguide structure to generate narrow-bandwidth radiation by thermal energy. The waveguide structure is designed to match the absorption wavelength ( $4.6 mu text{m}$ ) of the carbon monoxide $text{C}equiv text{O}$ bond. To optimize NBITE, different SiO2 thicknesses and heating temperatures were experimentally investigated. The full width at half maximum (FWHM) of the fabricated NBITE is $0.05 mu text{m}$ . On the other hand, the narrow-bandwidth infrared photodetector (NBIPD) has a Au $/$ amorphous-Si:H $/$ Au tri-layers structure with gold grating pattern on the top layer. The grating pattern is designed to absorb the $4.6 mu text{m}$ infrared wavelength emitted from NBITE. The amorphous-Si:H layer absorbs the infrared energy and changes its resistance. Therefore, the slope of NBIPD current versus time can be used to discriminate CO concentration. To experimentally evaluate the developed CO emitter $/$ detector, a prototype system for CO detection was also designed and implemented. Based on this system, CO can be detected down to 50 ppm, which is the permissible exposure limit suggested by Occupational Safety and Health Administration (OSHA).
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Sensing Performance and Optimizing Encapsulation Materials of a
           Coordinated Epoxy-Encapsulated Sensor for Strain Monitoring of Asphalt
           Pavement Layered Structures

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      Authors: Linping Su;Xuehao Luan;Zhengmei Qiu;Ming Liang;Yu Rong;Xue Xin;Zhanyong Yao;Chuanyi Ma;
      Pages: 9811 - 9823
      Abstract: The accurate mechanical response of asphalt pavement interlayer structure under complex environments still lacks reliable and durable real-time monitoring methods up to now. In this study, metal-foil strain gage, a mature and traditional stickup sensing element, was innovatively used as an embedded strain sensor to monitor asphalt mixture deformation by proposing the method of polymer encapsulated strain gage. The performance of encapsulating polymer was optimized and the effectiveness of sensor was studied. The DMP-30 was adopted to modify epoxy $/$ anhydride blends for strain gauge encapsulation, and dynamic mechanical analysis (DMA), thermogravimetric analysis (TGA) and Fourier transform infrared (FT-IR) spectroscopy were carried out. The results indicated that the encapsulating polymer with 1phr DMP-30 shows good modulus accommodation with asphalt pavement, and provides better thermal properties to adapt to the harsh environment of pavement monitoring. Benefiting from the encapsulated method and optimized encapsulating polymer, the sensor shows the same excellent sensing performance as the bare strain gage as well as good linearity and fatigue performance (more than 100,000 cycles at 200u $varepsilon $ ). Laboratory bending test of asphalt concrete with embedded sensor verified the high sensitivity coefficient and good survivability, which is accurate for micro strain monitoring. Meanwhile, numerical simulation confirmed the good compatibility and deformation coordination between the developed sensor and asphalt concrete. Therefore, the results of this study provide a new idea for accurate, long-term, and stable acquisition of dynamic response of pavement.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Millimeter-Wave Frequency Modulated Continuous Wave Radar-Based Soft Fall
           Detection Using Pattern Contour-Confined Doppler-Time Maps

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      Authors: Bo Wang;Zhi Zheng;Yong-Xin Guo;
      Pages: 9824 - 9831
      Abstract: Fall accidents are one of the leading causes of non-natural death of older people. It is necessary to design and implement fall detection systems in older people’s homes. Among all indoor fall detection approaches, radar-based methods are considered one of the optimum solutions. In this paper, a millimetre-wave frequency modulated continuous wave (FMCW) radar-based fall detection method using pattern contour-confined Doppler-time (PCC-DT) maps is proposed. The soft fall motions, which can lead to missed detections, are studied and analyzed. When Doppler-time (DT) maps are used to interpret different motions, the redundant information and outliers can cause detection errors. The proposed PCC-DT map can diminish the superfluous information and remove outlier points to improve detection accuracy. The experimental results show that the proposed method can detect sudden and soft fall motions with high accuracy, sensitivity, and specificity.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • An Accurate and Stable Extrinsic Calibration for a Camera and a 1D Laser
           Range Finder

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      Authors: Yuhong Tu;Yan Song;Fan Liu;Yuanxiu Zhou;Teya Li;Shuai Zhi;Yamin Wang;
      Pages: 9832 - 9842
      Abstract: Due to low cost and ease of manufacture, the combined sensor consisted of a camera and a 1D laser range finder is commonly used in many engineering applications. Especially in aerospace field, this type of combined sensor is important to earth observation and deep space exploration. This article proposes a novel extrinsic calibration method to get the accurate and stable calibration results of camera-1D laser range finder combined sensor. Firstly, an accuracy criterion named with directional comprehensive criterion is proposed to solve the less constraint in traditional calibration methods, which can evaluate the inconsistencies in the 1D laser ranging direction and the mean reprojection error in the 2D image plane direction fully. Then, according to the proposed directional comprehensive criterion, a novel robust extrinsic calibration framework is presented, which removes the observation data with large errors automatically and utilizes a stability criterion as the termination condition. The simulation experiments and real data experiments reveal that the proposed method is effective, which is superior to the existing methods.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Identification of Vehicle Dynamics Model and Lever-Arm for Arbitrarily
           Mounted Motion Sensor

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      Authors: Yoonjin Hwang;Yongseop Jeong;In So Kweon;Seibum B. Choi;
      Pages: 9843 - 9856
      Abstract: This paper presents a novel identification method for vehicle dynamics model and sensor lever-arm using the motion measurements from sensors mounted on arbitrary positions. Since known methods for vehicle model parameter identification and sensor lever-arm estimation have been cross-referencing the results from each other, a simple conjugation of two methods cannot solve the identification of model parameter and lever-arm concurrently. A modified single track model with normalized tire stiffness is formulated to decouple the lever-arm effect from the vehicle’s dynamics states. The identification scheme is conducted through an unscented Kalman filter by fusing the modified model with inertial and velocity measurements from the sensor. We demonstrate the efficacy of identification performance of the proposed method in simulations and real-vehicle experiments. The identified model accomplished the accuracy within 5% error for geometrical parameters and 10% error for tire stiffness over various experimental conditions and confirms the feasibility of utilizing motion estimation devices in vehicle dynamics and vice versa.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Near Infrared Sensor Setup for General Interface Detection in Automatic
           Liquid-Liquid Extraction Processes

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      Authors: Rodrigo Moreno;Andres Faina;Kasper Stoy;
      Pages: 9857 - 9867
      Abstract: This work presents a novel sensor setup for the general detection of liquid-liquid interfaces in different mixes of liquids as part of a liquid-liquid extraction device. The sensor setup is applied to a laboratory scale separatory funnel. It uses a near infrared sensor array which receives light going through the liquids inside the funnel, which are illuminated by a light source located on the other side and below the funnel. Light refracts inside the funnel and the liquids and reflects on the interface creating changing patterns in the light intensity measured by the sensor, providing a way of locating the liquid-liquid interface. Liquid mixes with different optical features, from transparent to opaque, emulsion and clean, are used to test whether different types of interfaces produce a distinguishable response on the sensor, allowing to detect interfaces in different situations that can occur as part of an Artificial Intelligence orchestrated battery chemical synthesis process. Emulsion interfaces create a discernible change in the sensor input by lowering the light intensity registered when crossing in front of the sensor making them easier to locate than with other optical techniques. The setup opens the possibility of detecting a liquid-liquid interface as it is forming and can be miniaturized to be attached to laboratory funnels as a manual aid or used with other transparent vessels in automatic solutions like liquid handling robots or pipetting robots.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Dedicated Tool Frame Based Tongue Interface Layout Improves 2D Visual
           Guided Control of an Assistive Robotic Manipulator: A Design Parameter for
           Tele-Applications

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      Authors: Ásgerður Arna Pálsdóttir;Mostafa Mohammadi;Bo Bentsen;Lotte N. S. Andreasen Struijk;
      Pages: 9868 - 9880
      Abstract: It is crucial to increase the independence of severely disabled individuals. Assistive robotics can aid in the desired activities of daily living, including tasks requiring remote performance e.g. grasping remote objects, turning switches on/off, and opening/closing doors. The robot control is compromised by the lack of efficient interfaces for individuals with disabilities and the lack of depth perception. This paper addresses these challenges by presenting the development and evaluation of efficient tongue-based robot interfaces and low-level robot control schemes targeting tele-robotic control through a 2D display. Ten able-bodied participants were successful in completing ten rounds of controlling a JACO robot to perform a pouring water task, using five different control methods, under 2D or 3D visual feedback. The tool-frame based tongue interface layout, L2_TF (with emulated joystick, mode switch button and a “GO” button) improved the 2D visual guided control of the JACO robot compared with the other tongue control methods. The mean trajectory length of completing the task using L2_TF was 3% longer compared with the standard joystick when controlling through 2D. The trajectory length for reaching and grabbing a bottle was shortest for L2_TF compared with all other control methods, including the joystick. The iTongue control layouts performed well in gripping time, showing no significant difference between 2D and 3D. The transition from 2D to 3D resulted in a mean decrease of 27.7% for task completion time across all interfaces. L2_TF and the joystick had the strongest and most similar robustness to the transition between 3D and 2D.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Energy-Efficient Mobile Sink-Based Intelligent Data Routing Scheme for
           Wireless Sensor Networks

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      Authors: Vaibhav Agarwal;Shashikala Tapaswi;Prasenjit Chanak;
      Pages: 9881 - 9891
      Abstract: Wireless Sensor Networks (WSNs) have become an indistinguishable part of any Internet of Things (IoT) based system. In an IoT-based system, WSN monitors different physical objects and forwards the collected data to the base station or gateway node for further processing. Existing routing protocols designed for WSNs are not suitable for IoT-based systems. An intelligent and high-performance routing protocol is essential for real-time data analysis and decision-making. Therefore, this paper proposes a mobile sink-based intelligent data routing scheme for WSNs. Initially, Particle Swarm Optimization is used for optimal cluster formation. After cluster formation, the optimal number of rendezvous points are selected, and a data-gathering tour is planned for the mobile sink. Furthermore, a mobile sink-based intelligent data gathering scheme is proposed to collect the data from the cluster heads. Extensive simulations and mathematical analysis are performed to verify the effectiveness of the proposed scheme. The simulation results are compared with state-of-the-art algorithms in terms of stability period, network lifetime, throughput, average energy consumption, fairness index, data transmission latency, and message overhead.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Energy Harvesting in Immersed Tunnel for Powering Wireless Sensor Nodes
           for Corrosion Monitoring

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      Authors: Jaamac Hassan Hire;Nikolaos Agianniotis;Brian Peter Kofoed;Farshad Moradi;
      Pages: 9892 - 9903
      Abstract: Collecting data from corrosion sensors in reinforced concrete structures demands intensive labor work, therefore measurements are only performed occasionally. A low-cost Wireless Sensor Network/Node (WSN) will eliminate the need for manual work and allow for continuous measurements if needed. For a distributed WSN over a large area, a concerning issue is how to power such devices. This paper, therefore, investigates the use of a reinforced concrete battery for powering WSNs. Results obtained from a real-world immersed tunnel, which has hundreds of electrochemical based corrosion sensors embedded into the reinforced concrete structure, shows that sufficient energy can be harvested from the sensors, to perform wireless transmission of corrosion data to a base-station. With an open circuit potential of 975 mV, the maximum harvested output power is $12.4~mu text{W}$ , while the minimum measured output power is $1~mu text{W}$ . The results also show that $8.82~mu text{W}$ , with an open circuit potential of 727 mV, can be directly harvested from the reinforcement steel itself. Due to the fact that the steel volume can work as a large battery anode, a longer lifetime for the energy source is expected. Furthermore, we show that the harvested energy from the corrosion sensors will induce a galvanic corrosion rate of only $3.7~mu text{m}$ /year, when transmitting the corrosion data once a month. This indicates that there is no risk to the structural integrity when using this energy source.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Toward a Robust Estimation of Respiratory Rate Using Cardiovascular
           Biomarkers: Robustness Analysis Under Pain Stimulation

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      Authors: Ziqiang Xu;Toshiki Sakagawa;Akira Furui;Shumma Jomyo;Masanori Morita;Masamichi Ando;Toshio Tsuji;
      Pages: 9904 - 9913
      Abstract: Respiration can modulate the cardiovascular system through the autonomic nervous system (ANS), deriving numerous methods for monitoring respiration based on cardiovascular biomarkers. However, the sensitivity of the ANS to environmental changes can negatively affect these methods, which suggests the necessity to evaluate their performance in estimating respiratory rate (RR). This paper aims to propose a method for robust estimation of RR using a biodegradable piezoelectric sensor by analyzing the robustness differences of these biomarkers under pain stimulation. In an electrocutaneous stimulus experiment conducted with 15 participants, arterial pulse waves near the elbow and wrist were measured, as well as the electrocardiogram and fingertip photoplethysmogram. The robustness of six biomarkers was quantified using respiratory quality index (RQI) and mean absolute percentage error (MAPE). Heart rate derived from the arterial pulse wave near the elbow achieves the best robustness (RQI $=85.67$ ±12.84 %, MAPE $=2.22$ ±1.81 %) of all biomarkers, whereas pulse wave velocity (PWV) from the elbow to the wrist performs best (RQI $=70.39$ ±12.15 %, MAPE $=3.47$ ±1.69 %) of the three biomarkers of PWV. Therefore, the robustness of biomarkers varies, as does the same biomarker measured at different sites. Our results reveal the heterogeneity of respiratory modulation on the cardiovascular system and demonstrate the robustness of the biomarkers of the arterial pulse wave near th- elbow in estimating RR. This study can help smart wearables perfect respiratory monitoring and contribute a robust method for respiratory monitoring using a biodegradable piezoelectric sensor.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Porous Elastomer Based Wide Range Flexible Pressure Sensor for Autonomous
           Underwater Vehicles

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      Authors: Ensieh S. Hosseini;Moupali Chakraborty;Joshua Roe;Yvan Petillot;Ravinder S. Dahiya;
      Pages: 9914 - 9921
      Abstract: This work presents the design and implementation of a porous polydimethylsiloxane (PDMS)-based wide-range flexible pressure sensor for autonomous underwater vehicles. The capacitive sensor, with porous PDMS as dielectric, is encapsulated in bulk PDMS polymer. The fabricated sensor was evaluated over a wide pressure range (0-230 kPa), which is similar to pressures experienced up to approx. 23 m below the sea level. The sensors showed linear response when tested in air and near-linear response (98%) when submerged in water. The sensor showed much higher sensitivity (0.375 kPa−1) in water than in the air environment. However, the sensor exhibited the performance and sensitivity similar to the air condition (0.005 kPa−1) when the readout electronics (encapsulated inside a watertight enclosure) was also submerged inside the water along with the sensor. The fabricated sensor also exhibited fast response and recovery time (190 ms), as well as excellent repeatability and stability (no drift) over tested range of 50 loading and unloading cycles. These results demonstrate the suitability of presented sensors for potential use in applications requiring a wide range of pressure, particularly the underwater robotics where real-time pressure monitoring is critical for autonomous operation.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Surgeon’s Habits-Based Novel Master Manipulator for the Vascular
           Interventional Surgical Master-Slave Robotic System

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      Authors: Wei Zhou;Shuxiang Guo;Jin Guo;Fanxu Meng;Zhengyang Chen;Chuqiao Lyu;
      Pages: 9922 - 9931
      Abstract: A master-slave vascular interventional surgical robotic system (MSVISRs) promises to treat cardio-cerebrovascular diseases without damaging the health of surgeons. Although many scholars are engaged in the research on the slave manipulator for the MSVISRs, there are very few studies on the master manipulator. In this study, a surgeon’s habits-based novel master manipulator is developed. This master manipulator imitates the operating habits of surgeons in surgery and uses a non-contact method with an optical mouse sensor to measure the operating displacements. The novelty of this approach is that this master manipulator with smaller size and non-contact displacement measurement method can provide the axial force and the circumferential force feedback independently. In this master manipulator, the rigid-flexible coupling structure is used to provide the axial force feedback. In addition, the brush DC motor is used to give the circumferential force feedback. Furthermore, the proposed master manipulator is calibrated and evaluated by experiments. The calibration experiments show that the maximum identification ranges for the axial force and circumferential force in the proposed master manipulator are 0.247-4.5N and 0.52-4.3N, respectively. Moreover, the evaluation experiments show that the maximum error is 0.8 mm in the axial direction. As compared with other master manipulator, the comprehensive properties of this novel master manipulator are shown to be better and more promising.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Soft Pressure Sensor for Underwater Sea Lamprey Detection

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      Authors: Hongyang Shi;Ian González-Afanador;Christopher Holbrook;Nelson Sepúlveda;Xiaobo Tan;
      Pages: 9932 - 9944
      Abstract: In this paper, an economical and effective soft pressure sensor for underwater sea lamprey detection is proposed, which consists of an array of piezoresistive elements between two layers of perpendicular copper tape electrodes, forming a passive resistor network. With multiplexers, the apparent resistance corresponding to each pixel of the sensing matrix can be measured directly, where the pixel is identified with the row and the column of the respective electrodes. However, this measured two-point resistance is not equal to the actual cell resistance for that pixel due to the crosstalk effect in the resistor network. Since the cell resistance reflects directly the pressure applied on each pixel, the relationship between the cell resistance and the measured two-point resistance is analyzed for a passive matrix of any size. More importantly, several regularized least-squares algorithms are proposed to reconstruct the cell resistance profile from the two-point resistance measurements, with enhanced robustness of the reconstruction in the presence of measurement noises and modeling errors. The proposed pressure sensor is applied to detect the suction attachment of sea lampreys, a devastating invasive species in the Great Lakes region. Experimental results demonstrate that the pressure sensor can successfully capture the rim profile of the lamprey’s sucking mouth. Moreover, the performance and computational complexity of the reconstruction algorithms with different regularization functions are compared.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A High Dynamic Range Vibration Radar Sensor With Automatic DC Voltage
           Extraction

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      Authors: Wei Ma;Dongyang Tang;Haitao Cui;Meiyu Wang;Zhiming Xiao;Changzhi Li;Weibo Hu;
      Pages: 9945 - 9955
      Abstract: One challenge of using a homodyne receiver to obtain accurate vibration information is the undesired DC voltage in a continuous wave radar. It reduces the output dynamic range and even saturates the signal path. In this paper, an adaptive DC extraction method with flexible clocks is proposed in a 5.8 GHz Doppler radar to separate the DC component from the input signal. Rather than simply eliminating the DC component, the proposed method digitizes the DC component as well as the input AC signal with a large dynamic range. It is accomplished by a mixed-signal feedback loop and features an excellent accommodation to large input DC variations and flexible settling time. In the loop, a closed-loop amplifier is used as the input stage and an ADC is followed to digitize the amplified quadrature signals from the radar. Afterward, a simplified digital filter is cascaded to extract the digital version of the DC component and feedback to the input stage. In this way, both the DC component and AC component in the input signal are separated and digitized without saturation. For verification, several simulations and experiments were conducted. The results show that a wide DC range can be tolerated and extracted. What’s more, the target motion with sub-millimeter amplitude can be successfully captured based on the proposed DC extraction loop.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Deep-q-Networks-Based Adaptive Dual-Mode Energy-Efficient Routing in
           Rechargeable Wireless Sensor Networks

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      Authors: Haobo Guo;Runze Wu;Bing Qi;Chen Xu;
      Pages: 9956 - 9966
      Abstract: In order to enhance the sustainability of rechargeable wireless sensor networks (RWSN), a deep-q-networks (DQN)-based adaptive dual-mode energy-efficient routing is proposed in this paper. Firstly, the life expectancy of each node is calculated based on multiple related factors, and a multi-hop routing based on forward transmission principle is proposed by using the indicator. Then according to the relationship between the life expectancy of a single node and the average life expectancy of the whole network, an adaptive dual-mode energy-efficient routing is proposed, which combines the multi-hop routing and the direct upload routing. Finally, for reducing the requirement of the single node for the network state information in the process of routing mode selection, a reinforcement learning framework based on DQN is designed, enabling the nodes to learn to judge the above relationship of life expectancy based on partial state information of its local network. Simulation results show that dynamic adjustment of the routing mode enables our algorithm to effectively optimize energy efficiency, so that the network lifetime increases obviously. Based on the limited information, the correct rate of routing mode selection can reach 95%, which ensures the applicability of our algorithm.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Toward Data Authenticity and Integrity for Blockchain-Based Mobile Edge
           Computing

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      Authors: Tianchen Ma;Bowen Du;Mianhong Li;Jiangfeng Li;Yang Shi;Hongfei Fan;
      Pages: 9967 - 9980
      Abstract: Blockchain-based mobile edge computing (BMEC) solves the problem of limited computing resources of devices in the Internet of Things (IoT). However, there are some security threats in the blockchain environment, among which the attacks against consensus algorithms are particularly serious, such as double-spending attacks and long-range attacks. These attacks target the block proposal or validation process, which compromise the integrity of the BMEC by overwriting the correct block record with the wrong block record. In this article,we propose a scheme to solve the above problem by using the cooperative threshold signature and group management scheme to protect the block validity. The blockchain process of a single node is controlled in a group cooperative way, and each new block is regarded as a valid block only if it has a valid threshold signature for the group to which it belongs. Concretely, the system is initialized by a cooperative distributed key generation protocol, the device management protocol uses a resident node to ensure the security and efficiency of device join and leave, and the signature issuing protocol can tolerate a certain degree of exceptions of nodes within the group. We analyze the resistance ability of the scheme against consensus attacks, prove the security of the scheme, and analyze the computing and communication efficiency. Experimental evaluations on the protocols of the proposed scheme have been conducted on cloud virtual machines and embedded boards, including Raspberry Pi and UP2 Grove, which indicated that the scheme is efficient in practical scenarios.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Modeling Classroom Occupancy Using Data of WiFi Infrastructure in a
           University Campus

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      Authors: Iresha Pasquel Mohottige;Hassan Habibi Gharakheili;Tim Moors;Vijay Sivaraman;
      Pages: 9981 - 9996
      Abstract: Universities worldwide are experiencing a surge in enrollments, therefore campus estate managers are seeking continuous data on attendance patterns to optimize the usage of classroom space. As a result, there is an increasing trend to measure classroom attendance by employing various sensing technologies, among which pervasive WiFi infrastructure is seen as a low-cost method. In a dense campus environment, the number of connected WiFi users does not well estimate room occupancy since connection counts are polluted by adjoining rooms, outdoor walkways, and network load balancing. This paper develops machine learning-based models, including unsupervised clustering and a combination of classification and regression algorithms, to infer classroom occupancy from WiFi sensing infrastructure. Our contributions are three-fold: (1) We analyze metadata from a dense and dynamic wireless network comprising of thousands of access points (APs) to draw insights into coverage of APs, the behavior of WiFi-connected users, and challenges of estimating room occupancy; (2) We propose a method to automatically map APs to classrooms and evaluate K-means, Expectation-Maximization (EM-GMM) and Hierarchical Clustering (HC) algorithms; and (3) We model classroom occupancy and evaluate varying algorithms, namely Logistic Regression, Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), Linear Regression (LR) and Support Vector Regression (SVR). We achieve 84.6% accuracy in mapping APs to classrooms, while our estimation for room occupancy (with symmetric Mean Absolute Percentage Error (sMAPE) of 13.10%) is comparable to beam counter sensors.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Identify Selective Forwarding Attacks Using Danger Model: Promote the
           Detection Accuracy in Wireless Sensor Networks

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      Authors: Xinyu Huang;Yuanming Wu;
      Pages: 9997 - 10008
      Abstract: Wireless sensor networks (WSNs) are prone to attack due to open work conditions and broadcast communication. The selective forwarding attack, one of the inner attacks in WSNs, is the hardest attack to detect among denial of service (DoS) attacks. The malicious nodes which launch the selective forwarding attack will drop part of or all the data packets they received. Many proposed detection methods against selective forwarding attacks have low accuracy or high algorithm complexity, especially when the attacker works its way in the network along with several attacks, such as blackhole, wormhole, and Distributed Denial of Service (DDoS). Here, an artificial immune system based on the danger model is established to detect network attacks. To promote detection accuracy and reduce computation, we have proposed a screen-confirm scheme. In the screening phase, the scheme first obtains the danger signals from nodes’ energy consumption, forwarding rate, connect duration, transmission frequency, and transmission time, then it screens out the suspected selective forwarding attacks from DoS attacks using a support vector machine (SVM). After that, in the confirming phase, we select an optimal danger threshold and calculate the outputs of the suspected ones, then confirm them by comparing outputs and threshold. The simulation results show that our scheme’s missing detection rate (MDR) is close to 1.3% and keeps the false detection rate (FDR) lower than 4.3% when the malicious ratio is 10%. Moreover, compared with other related work, our proposed method offers a lower algorithm complexity.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Channel-Aware Gait-Cycle-Based Transmission in Wireless Body Area Networks

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      Authors: Vinicius C. Ferreira;Célio Albuquerque;Débora Christina Muchaluat-Saade;
      Pages: 10009 - 10017
      Abstract: The use of the Internet of Things has proven to be an alternative for health monitoring, providing less discomfort to patients and good cost-benefit. To fully exploit the benefits of wireless technologies in e-health, the IEEE 802.15.6 standard for Wireless Body Area Networks (WBAN) has been created. However, technical and social challenges must be addressed to enable their adoption. Some factors, such as the use of the human body as a propagation media, and human body movements, make WBAN a new paradigm of wireless communication networks. The human body movement and posture affect the wireless channel quality, which may result in poor communication performance. To meet the requirements of WBAN applications, while preserving the energy efficiency, this paper proposes a Channel Aware Gait-cycle-based transmission mechanism (CAG), a mechanism that uses human body movement and channel response correlation to transmit during good channel conditions, ensuring reliability and energy savings. Our proposal was analyzed in the Castalia Simulator and compared against TDMA-based scheduling and the IEEE 802.15.6 CSMA/CA protocol. Simulation results show CAG significantly improves packet delivery ratio and energy efficiency.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • A Node Deployment Optimization Algorithm of WSNs Based on Improved Moth
           Flame Search

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      Authors: Yindi Yao;Shanshan Hu;Ying Li;Qin Wen;
      Pages: 10018 - 10030
      Abstract: Wireless sensor networks, one of the basic technologies of remote environmental monitoring, can provide efficient sensing and communication services under limited energy supply. Coverage control is an important method to ensure efficient communication and reliable data transmission. Given the complex physical environments, which impede the energy supplement and recovery of sensor nodes, the motivation of our research is to repair the coverage holes and reduce the energy consumption during the deployment of sensor nodes. Firstly, the variable spiral position update and the adaptive inertia weight strategy are adopted to improve local development and global search ability of the moth flame algorithm. Secondly, we analyze the virtual force of nodes, including the attractive force of uncovered grid points, the virtual force between adjacent sensor nodes and the repulsive force of boundary. The node resultant force is used as the disturbance factor of moth position updating to optimize the path, which effectively avoids the “premature” problem of the algorithm and accelerates global convergence. Finally, moth search is used to guide nodes to move to the area with coverage holes to achieve coverage optimization. In addition, we limit the random walking range of moths to reduce the moving distance. The simulation results show that compared with VFPSO, VFA and MFO algorithms, the coverage rate of VF-IMFO algorithm is increased by 7.16%, 3.85% and 22.2%, and the average moving distance of nodes is reduced by 9.01 $textbf {m}$ , 0.51 $textbf {m}$ and 32.46 $textbf {m}$ respectively. Moreover, under different deployment environments, the VF-IMFO algorithm still main-ains remarkable performance advantages.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Corrections to “A Human-in-the-Loop Probabilistic CNN-Fuzzy Logic
           Framework for Accident Prediction in Vehicular Networks”

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      Authors: Muhammad Usman;Anil Carie Chettupally;Bhaskar Marapelli;Hayat Dino Bedru;Kamanashish Biswas;
      Pages: 10031 - 10031
      Abstract: In the above article [1], the surname Chettupally of the author Anil Carie Chettupally was inadvertently omitted from the authors list when the article was originally published.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • IEEE Sensor Journal cover/frontispiece competition

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      Pages: 10032 - 10032
      Abstract: Presents information on the IEEE Sensor Journal cover/frontispiece competition.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
  • Introducing IEEE Collabratec

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      Pages: 10033 - 10033
      Abstract: Advertisement.
      PubDate: May15, 15 2022
      Issue No: Vol. 22, No. 10 (2022)
       
 
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