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Sensors, Volume 21, Issue 7 (April-1 2021) – 319 articles

Cover Story (view full-size image): In smart cities, spatio-temporal interpolation provides a fine-grained understanding of local phenomena, such as weather, air quality, or traffic data, offering estimates of observations in unobserved locations and time slots. However, with the ever-increasing sensor data, the data transmission and processing requirements of the predominantly centralized architectures have become unfeasible. To address this scaling problem, we propose EDISON: algorithms for distributed learning and inference, and an edge-native architecture for distributing the data and the computations between device, edge and cloud layers. The results show that EDISON provides an improvement over alternative approaches, reaching at best a 10% smaller RMSE than a global interpolation, and a 6% smaller RMSE than a baseline-distributed approach. View this paper.
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15 pages, 1898 KiB  
Article
A Comprehensive Comparison and Validation of Published Methods to Detect Turn Switch during Alpine Skiing
by Aaron Martínez, Cory Snyder, Stephanie R. Moore and Thomas Stöggl
Sensors 2021, 21(7), 2573; https://doi.org/10.3390/s21072573 - 6 Apr 2021
Cited by 6 | Viewed by 2900
Abstract
The instant of turn switch (TS) in alpine skiing has been assessed with a variety of sensors and TS concepts. Despite many published methodologies, it is unclear which is best or how comparable they are. This study aimed to facilitate the process of [...] Read more.
The instant of turn switch (TS) in alpine skiing has been assessed with a variety of sensors and TS concepts. Despite many published methodologies, it is unclear which is best or how comparable they are. This study aimed to facilitate the process of choosing a TS method by evaluating the accuracy and precision of the methodologies previously used in literature and to assess the influence of the sensor type. Optoelectronic motion capture, inertial measurement units, pressure insoles, portable force plates, and electromyography signals were recorded during indoor treadmill skiing. All TS methodologies were replicated as stated in their respective publications. The method proposed by Supej assessed with optoelectronic motion capture was used as a comparison reference. TS time differences between the reference and each methodology were used to assess accuracy and precision. All the methods analyzed showed an accuracy within 0.25 s, and ten of them within 0.05 s. The precision ranged from ~0.10 s to ~0.60 s. The TS methodologies with the best performance (accuracy and precision) were Klous Video, Spörri PI (pressure insoles), Martinez CTD (connected boot), and Yamagiwa IMU (inertial measurement unit). In the future, the specific TS methodology should be chosen with respect to sensor selection, performance, and intended purpose. Full article
(This article belongs to the Section Physical Sensors)
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4 pages, 172 KiB  
Editorial
Biomedical Photoacoustic Imaging and Sensing Using Affordable Resources
by Mithun Kuniyil Ajith Singh and Wenfeng Xia
Sensors 2021, 21(7), 2572; https://doi.org/10.3390/s21072572 - 6 Apr 2021
Cited by 4 | Viewed by 2607
Abstract
The photoacoustic (PA) effect, also called the optoacoustic effect, was discovered in the 1880s by Alexander Graham Bell and has been utilized for biomedical imaging and sensing applications since the early 1990s [...] Full article
(This article belongs to the Special Issue Biomedical Photoacoustic Imaging and Sensing Using Affordable Resources)
28 pages, 3214 KiB  
Article
Semantic Interoperability between IEC 61850 and oneM2M for IoT-Enabled Smart Grids
by Salvatore Cavalieri
Sensors 2021, 21(7), 2571; https://doi.org/10.3390/s21072571 - 6 Apr 2021
Cited by 14 | Viewed by 3826
Abstract
In the era of Industry 4.0, pervasive adoption of communication technologies based on the Internet of Things represents a very strong requirement in several domains. In the smart grid domain, there is the need to overcome one of the main limitations of the [...] Read more.
In the era of Industry 4.0, pervasive adoption of communication technologies based on the Internet of Things represents a very strong requirement in several domains. In the smart grid domain, there is the need to overcome one of the main limitations of the current electric grid, allowing the use of heterogeneous devices capable of measuring, monitoring and exchanging information about grid components. For this reason, current literature often presents research activities about enabling internet of things (IoT) in smart grids; in particular, several proposals aim to realize interworking between IoT and smart grid communication standards, allowing exchange of information between IoT devices and the electrical grid components. Semantic interoperability should be achieved in an interworking solution in order to provide a common meaning of the data exchanged by heterogeneous devices, even if they belong to different domains. Until now, semantic interoperability remains an open challenge in the smart grid field. The paper aims to propose a novel solution of interworking between two of the most used communication systems in smart grids and IoT domains, i.e., IEC 61850 and oneM2M, respectively. A semantic interoperability solution is also proposed to be used in the interworking scheme here presented. Full article
(This article belongs to the Special Issue Industrial Internet of Things in the Industry 4.0: New Researches, Applications and Challenges)
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15 pages, 20227 KiB  
Article
Response of Transitional Mixtures Retaining Memory of In-Situ Overburden Pressure Monitored Using Electromagnetic and Piezo Crystal Sensors
by Sang Yeob Kim, Jong-Sub Lee and Junghee Park
Sensors 2021, 21(7), 2570; https://doi.org/10.3390/s21072570 - 6 Apr 2021
Cited by 1 | Viewed by 2515
Abstract
The major and minor components in granular soil materials determine their properties and behavior. This study explores the transitional behavior within threshold fines fraction of soil mixtures based on the data from the literature and experiments. From the literature survey, the void ratio, [...] Read more.
The major and minor components in granular soil materials determine their properties and behavior. This study explores the transitional behavior within threshold fines fraction of soil mixtures based on the data from the literature and experiments. From the literature survey, the void ratio, shear wave velocity, compression index, and friction angle capture the transitional turning point between the low and data-adjusted high threshold fines fractions. In particular, there is a dramatic change in hydraulic conductivity below the low threshold fines fraction that highlights the critical role of small amounts of fines in the fluid flow (e.g., clogging). From an experimental study, the engineering properties of natural soil samples identified using deformation and elastic wave sensors show transitional trends within the Revised Soil Classification System framework. The evolution of compressibility and shear wave velocity indicate that either coarse, fine, or both particles are likely to contribute to large and small strain stiffnesses when the effective stress is below 400 kPa. Thereafter, both engineering properties indicate that the soil sample retains a memory of in-situ overburden pressure when the effective stress is around 400 kPa. There is a critical role of fines that are slightly higher than low threshold fines fraction on engineering properties that promote the application of Revised Soil Classification System RSCS to natural soils. Full article
(This article belongs to the Special Issue Emerging Characterization of Geomaterials Using Advanced Geo-Sensors)
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23 pages, 6255 KiB  
Article
Complete Automation of an Energy Consumption Reduction Strategy from a Water Treatment and Distribution Facility, Inside an Industrial Internet of Things-Compliant Proactive Historian Application
by Andrei Nicolae, Adrian Korodi and Ioan Silea
Sensors 2021, 21(7), 2569; https://doi.org/10.3390/s21072569 - 6 Apr 2021
Cited by 7 | Viewed by 2670
Abstract
The Industrial Internet of Things and Industry 4.0 paradigms are steering the industrial landscape towards better connected entities, superior interoperability and information exchange, which lays the basis for developing more intelligent solutions that are already starting to bring numerous benefits. The current research [...] Read more.
The Industrial Internet of Things and Industry 4.0 paradigms are steering the industrial landscape towards better connected entities, superior interoperability and information exchange, which lays the basis for developing more intelligent solutions that are already starting to bring numerous benefits. The current research aligns to this course, in an attempt to build an automated and autonomous software tool, capable of reducing the energy consumption of a water treatment and distribution facility, by optimizing the water sources usage. Based on several previous researches, the present paper details both the complete automation of the optimizing strategy inside a proactive historian application and the tests executed with the finished solution. Possessing the abilities to directly influence the monitored system in a non-invasive manner, and to link all the sequences of the algorithm automatically, the solution is now ready for long-term functioning without any external interference. Full article
(This article belongs to the Special Issue Sensors and Real Time Systems for IIoT)
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17 pages, 41705 KiB  
Article
Common-Mode Voltage Reduction in Capacitive Sensing of Biosignal Using Capacitive Grounding and DRL Electrode
by Tadeas Bednar, Branko Babusiak, Michal Labuda, Milan Smetana and Stefan Borik
Sensors 2021, 21(7), 2568; https://doi.org/10.3390/s21072568 - 6 Apr 2021
Cited by 5 | Viewed by 3662
Abstract
A capacitive measurement of the biosignals is a very comfortable and unobtrusive way suitable for long-term and wearable monitoring of health conditions. This type of sensing is very susceptible to noise from the surroundings. One of the main noise sources is power-line noise, [...] Read more.
A capacitive measurement of the biosignals is a very comfortable and unobtrusive way suitable for long-term and wearable monitoring of health conditions. This type of sensing is very susceptible to noise from the surroundings. One of the main noise sources is power-line noise, which acts as a common-mode voltage at the input terminals of the acquisition unit. The origin and methods of noise reduction are described on electric models. Two methods of noise removal are modeled and experimentally verified in the paper. The first method uses a passive capacitive grounding electrode, and the second uses an active capacitive Driven Right Leg (DRL) electrode. The effect of grounding electrode size on noise suppression is experimentally investigated. The increasing electrode area reduces power-line noise: the power of power-line frequency within the measured signal is 70.96 dB, 59.13 dB, and 43.44 dB for a grounding electrode area of 1650 cm2, 3300 cm2, and 4950 cm2, respectively. The capacitive DRL electrode shows better efficiency in common-mode noise rejection than the grounding electrode. When using an electrode area of 1650 cm2, the DRL achieved 46.3 dB better attenuation than the grounding electrode at power-line frequency. In contrast to the grounding electrode, the DRL electrode reduces a capacitive measurement system’s financial costs due to the smaller electrode area made of the costly conductive textile. Full article
(This article belongs to the Special Issue Sensors, Circuit and System for Biomedical Applications)
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14 pages, 61494 KiB  
Article
Quantifying Hole-Edge Crack of Bolt Joints by Using an Embedding Triangle Eddy Current Sensing Film
by Shilei Fan, Junyan Yi, Hu Sun and Fenglin Yun
Sensors 2021, 21(7), 2567; https://doi.org/10.3390/s21072567 - 6 Apr 2021
Cited by 5 | Viewed by 3124
Abstract
Hole-edge crack quantification of bolt joints is critical for monitoring and estimating structural integrity of aircraft. The paper proposes a new triangle eddy current sensor array for the purpose of increasing the level of quantifying hole-edge crack parameters, especially, the crack angle. The [...] Read more.
Hole-edge crack quantification of bolt joints is critical for monitoring and estimating structural integrity of aircraft. The paper proposes a new triangle eddy current sensor array for the purpose of increasing the level of quantifying hole-edge crack parameters, especially, the crack angle. The new senor array consists of triangular coils instead of planar rectangular coils. The configuration of the novel sensor array, including the excitation current directions and the excitation winding shape, is optimized by simulation. The ability of the proposed sensing film to identify the crack parameters has been verified by finite element simulations and experiments. Results shows that triangular coils with same current directions in circumferentially adjacent coils and opposite current directions in axially adjacent coils achieve better performance in sensor linearity and resolution compared to rectangular coils. In addition, it has also been proved that the sensing film has a good potential to identify the crack depth and length. Full article
(This article belongs to the Special Issue Smart Sensors for Structural Health Monitoring and Nondestructive Evaluation)
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13 pages, 1592 KiB  
Article
Gas Damping in Capacitive MEMS Transducers in the Free Molecular Flow Regime
by Boris A. Boom, Alessandro Bertolini, Eric Hennes and Johannes F. J. van den Brand
Sensors 2021, 21(7), 2566; https://doi.org/10.3390/s21072566 - 6 Apr 2021
Cited by 3 | Viewed by 2882
Abstract
We present a novel analysis of gas damping in capacitive MEMS transducers that is based on a simple analytical model, assisted by Monte-Carlo simulations performed in Molflow+ to obtain an estimate for the geometry dependent gas diffusion time. This combination provides results with [...] Read more.
We present a novel analysis of gas damping in capacitive MEMS transducers that is based on a simple analytical model, assisted by Monte-Carlo simulations performed in Molflow+ to obtain an estimate for the geometry dependent gas diffusion time. This combination provides results with minimal computational expense and through freely available software, as well as insight into how the gas damping depends on the transducer geometry in the molecular flow regime. The results can be used to predict damping for arbitrary gas mixtures. The analysis was verified by experimental results for both air and helium atmospheres and matches these data to within 15% over a wide range of pressures. Full article
(This article belongs to the Section Electronic Sensors)
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19 pages, 2810 KiB  
Article
A Comparative Study of BDS Triple-Frequency Ambiguity Fixing Approaches for RTK Positioning
by Huizhong Zhu, Yangyang Lu, Longjiang Tang, Jun Li, Aigong Xu and Maorong Ge
Sensors 2021, 21(7), 2565; https://doi.org/10.3390/s21072565 - 6 Apr 2021
Cited by 4 | Viewed by 2502
Abstract
Concerning the triple-frequency ambiguity resolution, in principle there are three different realizations. The first one is to fix all the ambiguities of the original frequencies together. However, it is also believed that fixing the combined integer ambiguities with longer wavelength, such as extra-wide-lane [...] Read more.
Concerning the triple-frequency ambiguity resolution, in principle there are three different realizations. The first one is to fix all the ambiguities of the original frequencies together. However, it is also believed that fixing the combined integer ambiguities with longer wavelength, such as extra-wide-lane (EWL), wide-lane (WL), should be advantageous. Also, it is demonstrated that fixing sequentially EWL, WL and one type of original ambiguities provides better results, as the previously fixed ambiguities increase parameters’ precision for later fixings. In this paper, we undertake a comparative study of the three fixing approaches by means of experimental validation. In order to realize the three fixing approaches from the same information in terms of adjustment, we developed a processing strategy to provide fully consistent normal equations. We first generate the normal equation with the original undifferentiated carrier phase ambiguities, then map it into that with the combined and double-differenced ambiguities required by the individual approach for fixing. Four baselines of 258 m, 22 km, 47 km and 53 km are selected and processed in both static and kinematic mode using the three ambiguity-fixing approaches. Indicators including time of first fixed solution (TFFS), the correct fixing rate, positioning accuracy and RATIO are used to evaluate and investigate results. We also made a preliminary theoretical explanation of the results by looking into the decorrelation procedure of the ambiguity searching algorithm and the intermediate results. As conclusions, integrated searching of original ambiguities or combined ambiguities has almost the same fixing performance, whereas the sequential fixing of EWL, WL and B1 ambiguities overperforms the integrated searching. By the way, the third-frequency data can shorten the TFFS significantly but can hardly improve the positioning. Full article
(This article belongs to the Special Issue Signal Processing for GPS/GNSS/APNT Systems)
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20 pages, 8614 KiB  
Article
Low Field Optimization of a Non-Contacting High-Sensitivity GMR-Based DC/AC Current Sensor
by Cristian Mușuroi, Mihai Oproiu, Marius Volmer, Jenica Neamtu, Marioara Avram and Elena Helerea
Sensors 2021, 21(7), 2564; https://doi.org/10.3390/s21072564 - 6 Apr 2021
Cited by 19 | Viewed by 3807
Abstract
Many applications require galvanic isolation between the circuit where the current is flowing and the measurement device. While for AC, the current transformer is the method of choice, in DC and, especially for low currents, other sensing methods must be used. This paper [...] Read more.
Many applications require galvanic isolation between the circuit where the current is flowing and the measurement device. While for AC, the current transformer is the method of choice, in DC and, especially for low currents, other sensing methods must be used. This paper aims to provide a practical method of improving the sensitivity and linearity of a giant magnetoresistance (GMR)-based current sensor by adapting a set of design rules and methods easy to be implemented. Our approach utilizes a multi-trace current trace and a double differential GMR based detection system. This essentially constitutes a planar coil which would effectively increase the usable magnetic field detected by the GMR sensor. An analytical model is developed for calculating the magnetic field generated by the current in the GMR sensing area which showed a significant increase in sensitivity up to 13 times compared with a single biased sensor. The experimental setup can measure both DC and AC currents between 2–300 mA, with a sensitivity between 15.62 to 23.19 mV/mA, for biasing fields between 4 to 8 Oe with a detection limit of 100 μA in DC and 100 to 300 μA in AC from 10 Hz to 50 kHz. Because of the double differential setup, the detection system has a high immunity to external magnetic fields and a temperature drift of the offset of about −2.59 × 10−4 A/°C. Finally, this setup was adapted for detection of magnetic nanoparticles (MNPs) which can be used to label biomolecules in lab-on-a-chip applications and preliminary results are reported. Full article
(This article belongs to the Special Issue Magnetic Sensors 2021)
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18 pages, 2012 KiB  
Article
Find Outliers of Image Edge Consistency by Weighted Local Linear Regression with Equality Constraints
by Mingzhu Zhu, Yaoqing Hu, Junzhi Yu, Bingwei He and Jiantao Liu
Sensors 2021, 21(7), 2563; https://doi.org/10.3390/s21072563 - 6 Apr 2021
Cited by 2 | Viewed by 2585
Abstract
In this paper, we propose a general method to detect outliers from contaminated estimates of various image estimation applications. The method does not require any prior knowledge about the purpose, theory or hardware of the application but simply relies on the law of [...] Read more.
In this paper, we propose a general method to detect outliers from contaminated estimates of various image estimation applications. The method does not require any prior knowledge about the purpose, theory or hardware of the application but simply relies on the law of edge consistency between sources and estimates. The method is termed as ALRe (anchored linear residual) because it is based on the residual of weighted local linear regression with an equality constraint exerted on the measured pixel. Given a pair of source and contaminated estimate, ALRe offers per-pixel outlier likelihoods, which can be used to compose the data weights of post-refinement algorithms, improving the quality of refined estimate. ALRe has the features of asymmetry, no false positive and linear complexity. Its effectiveness is verified on four applications, four post-refinement algorithms and three datasets. It demonstrates that, with the help of ALRe, refined estimates are better in the aspects of both quality and edge consistency. The results are even comparable to model-based and hardware-based methods. Accuracy comparison on synthetic images shows that ALRe could detect outliers reliably. It is as effective as the mainstream weighted median filter at spike detection and is significantly better at bad region detection. Full article
(This article belongs to the Section Sensing and Imaging)
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21 pages, 55664 KiB  
Article
Application of the Gaussian Mixture Model to Classify Stages of Electrical Tree Growth in Epoxy Resin
by Abdullahi Abubakar Mas’ud, Arunachalam Sundaram, Jorge Alfredo Ardila-Rey, Roger Schurch, Firdaus Muhammad-Sukki and Nurul Aini Bani
Sensors 2021, 21(7), 2562; https://doi.org/10.3390/s21072562 - 6 Apr 2021
Cited by 5 | Viewed by 2873
Abstract
In high-voltage (HV) insulation, electrical trees are an important degradation phenomenon strongly linked to partial discharge (PD) activity. Their initiation and development have attracted the attention of the research community and better understanding and characterization of the phenomenon are needed. They are very [...] Read more.
In high-voltage (HV) insulation, electrical trees are an important degradation phenomenon strongly linked to partial discharge (PD) activity. Their initiation and development have attracted the attention of the research community and better understanding and characterization of the phenomenon are needed. They are very damaging and develop through the insulation material forming a discharge conduction path. Therefore, it is important to adequately measure and characterize tree growth before it can lead to complete failure of the system. In this paper, the Gaussian mixture model (GMM) has been applied to cluster and classify the different growth stages of electrical trees in epoxy resin insulation. First, tree growth experiments were conducted, and PD data captured from the initial to breakdown stage of the tree growth in epoxy resin insulation. Second, the GMM was applied to categorize the different electrical tree stages into clusters. The results show that PD dynamics vary with different stress voltages and tree growth stages. The electrical tree patterns with shorter breakdown times had identical clusters throughout the degradation stages. The breakdown time can be a key factor in determining the degradation levels of PD patterns emanating from trees in epoxy resin. This is important in order to determine the severity of electrical treeing degradation, and, therefore, to perform efficient asset management. The novelty of the work presented in this paper is that for the first time the GMM has been applied for electrical tree growth classification and the optimal values for the hyperparameters, i.e., the number of clusters and the appropriate covariance structure, have been determined for the different electrical tree clusters. Full article
(This article belongs to the Section Sensor Materials)
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27 pages, 6897 KiB  
Article
Indirect Temperature Measurement in High Frequency Heating Systems
by Alexander Oskolkov, Igor Bezukladnikov and Dmitriy Trushnikov
Sensors 2021, 21(7), 2561; https://doi.org/10.3390/s21072561 - 6 Apr 2021
Cited by 7 | Viewed by 4856
Abstract
One of the biggest challenges of fused deposition modeling (FDM)/fused filament fabrication (FFF) 3D-printing is maintaining consistent quality of layer-to-layer adhesion, and on the larger scale, homogeneity of material inside the whole printed object. An approach for mitigating and/or resolving those problems, based [...] Read more.
One of the biggest challenges of fused deposition modeling (FDM)/fused filament fabrication (FFF) 3D-printing is maintaining consistent quality of layer-to-layer adhesion, and on the larger scale, homogeneity of material inside the whole printed object. An approach for mitigating and/or resolving those problems, based on the rapid and reliable control of the extruded material temperature during the printing process, was proposed. High frequency induction heating of the nozzle with a minimum mass (<1 g) was used. To ensure the required dynamic characteristics of heating and cooling processes in a high power (peak power > 300 W) heating system, an indirect (eddy current) temperature measurement method was proposed. It is based on dynamic analysis over various temperature-dependent parameters directly in the process of heating. To ensure better temperature measurement accuracy, a series-parallel resonant circuit containing an induction heating coil, an approach of desired signal detection, algorithms for digital signal processing and a regression model that determines the dependence of the desired signal on temperature and magnetic field strength were proposed. The testbed system designed to confirm the results of the conducted research showed the effectiveness of the proposed indirect measurement method. With an accuracy of ±3 °C, the measurement time is 20 ms in the operating temperature range from 50 to 350 °C. The designed temperature control system based on an indirect measurement method will provide high mechanical properties and consistent quality of printed objects. Full article
(This article belongs to the Special Issue Next-Generation Temperature Sensors)
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15 pages, 4050 KiB  
Article
Construction of Ultrasonic Tactile Force Feedback Model in Teleoperation Robot System
by Yang Liu, Xiaoling Li, Jiarui Lai, Ziming Zheng, Huijin Zhu and Min Li
Sensors 2021, 21(7), 2560; https://doi.org/10.3390/s21072560 - 6 Apr 2021
Cited by 10 | Viewed by 3418
Abstract
The ultrasonic phased array as an emerging interactive tool is increasingly used for aerial tactile interaction. However, there is almost no method to achieve remote variable force feedback through the ultrasonic phased array as far as we know. This article presents a force [...] Read more.
The ultrasonic phased array as an emerging interactive tool is increasingly used for aerial tactile interaction. However, there is almost no method to achieve remote variable force feedback through the ultrasonic phased array as far as we know. This article presents a force tactile feedback method for teleoperating robot systems that tracks the five fingers and forms a focus on the fingertips. First, the perceived size of the focus depends on the input parameters. The influence of the parameters on the physical output pressure intensity was obtained through physical test experiments. Then, the absolute threshold and difference threshold of human perception were studied through psychophysical experimental methods. Finally, the input parameters were selected according to the experimental results. According to the collected data, the construction of the force regression model was completed, and different parameters were mapped to the perceived intensity. The contact force generated in the actual operation is fed back to the haptic system, and the constructed model automatically adjusts the control parameters to ensure that the user’s hand presents a sensory output corresponding to the intensity change. The entire force feedback system is evaluated, and results show that the system shows good perceptual quality. Full article
(This article belongs to the Section Physical Sensors)
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16 pages, 2764 KiB  
Article
Potentiometric Performance of a Highly Flexible-Shaped Trifunctional Sensor Based on ZnO/V2O5 Microrods
by Alfred Bekoe Appiagyei and Jeong In Han
Sensors 2021, 21(7), 2559; https://doi.org/10.3390/s21072559 - 6 Apr 2021
Cited by 5 | Viewed by 2589
Abstract
A trifunctional flexible sensor was fabricated on a polyethylene terephthalate (PET) fiber surface. Synthesized ZnO and ZnO/V2O5 composite were coated on ZnO seed layer sputtered PET fiber. X-ray diffraction (XRD) and photoelectron spectroscopy (XPS) techniques confirmed the exact formation of [...] Read more.
A trifunctional flexible sensor was fabricated on a polyethylene terephthalate (PET) fiber surface. Synthesized ZnO and ZnO/V2O5 composite were coated on ZnO seed layer sputtered PET fiber. X-ray diffraction (XRD) and photoelectron spectroscopy (XPS) techniques confirmed the exact formation of ZnO and ZnO/V2O5. The fabricated ZnO/V2O5 on ZnO seeds base temperature sensor recorded better electrical properties and reversibility with a maximum temperature coefficient resistance (TCR) of 0.0111 °C−1. A calibration curve (R = 0.9941) within glucose concentration of (10 µM–10 mM) was obtained at +0.8 V vs. Ag/AgCl from current-voltage curves which assisted in calculating glucose sensitivity, limit of detection (LOD), limit of quantification (LOQ). The electrode achieved an outstanding performance of sensitivity (72.06 µAmM−1cm−2), LOD (174 µM), and LOQ (582 µM) at optimum deposition time. Interference from oxidation of interfering biomolecules such as ascorbic acid, dopamine, and uric acid were negligible compared to glucose. Finally, the fabricated electrode was employed as a pH sensor and displayed a pH sensitivity of 42.26 mV/pH (R = 0.9922). This fabricated ZnO/V2O5 electrode exhibited high sensitivity and a stable combined temperature, glucose, and pH sensor which is promising for development of multifunctional sensors in next generation wearables. Full article
(This article belongs to the Section Sensor Materials)
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13 pages, 1081 KiB  
Article
Oxygen Sensing of Pt/PEO-TiO2 in Humid Atmospheres at Moderate Temperatures
by Bernd Engelkamp and Klaus Schierbaum
Sensors 2021, 21(7), 2558; https://doi.org/10.3390/s21072558 - 6 Apr 2021
Cited by 2 | Viewed by 2317
Abstract
Here, we show that the presence of adsorbed water improves the oxygen-sensing properties of Pt/TiO2 at moderate temperatures. The studied interface is based on porous plasma electrolytic oxidized titanium (PEO-TiO2) covered with platinum clusters. The electrical resistance across Pt/PEO-TiO2 [...] Read more.
Here, we show that the presence of adsorbed water improves the oxygen-sensing properties of Pt/TiO2 at moderate temperatures. The studied interface is based on porous plasma electrolytic oxidized titanium (PEO-TiO2) covered with platinum clusters. The electrical resistance across Pt/PEO-TiO2 is explained by an electronic depletion layer. Oxygen adsorbates further increase the depletion by inducing extrinsic interface states, which are occupied by TiO2 conduction band electrons. The high oxygen partial pressure in ambient air substantially limits the electron transport across the interface. Our DC measurements at defined levels of humidity at 30 ∘C show that adsorbed water counteracts this shortcoming, allowing oxygen sensing at room conditions. In addition, response and recovery times from temporal oxygen exposure decrease with humidity. We attribute the effects to competing adsorption processes and reactions of water with adsorbed oxygen species and/or lattice oxygen, which involve electron re-injection to the TiO2 conduction band. Elevated temperatures up to 170 ∘C attenuate the effects, presumably due to the lower binding strength to the surface of molecular water compared with oxygen adsorbates. Full article
(This article belongs to the Section Sensor Materials)
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25 pages, 6804 KiB  
Article
Design of Minimum Nonlinear Distortion Reconfigurable Antennas for Next-Generation Communication Systems
by Germán Augusto Ramírez Arroyave, Antoni Barlabé, Lluís Pradell, Javier Leonardo Araque Quijano, Bedri A. Cetiner and Luis Jofre-Roca
Sensors 2021, 21(7), 2557; https://doi.org/10.3390/s21072557 - 6 Apr 2021
Cited by 8 | Viewed by 3338
Abstract
Nonlinear effects in the radio front-end can degrade communication quality and system performance. In this paper we present a new design technique for reconfigurable antennas that minimizes the nonlinear distortion and maximizes power efficiency through the minimization of the coupling between the internal [...] Read more.
Nonlinear effects in the radio front-end can degrade communication quality and system performance. In this paper we present a new design technique for reconfigurable antennas that minimizes the nonlinear distortion and maximizes power efficiency through the minimization of the coupling between the internal switching ports and the external feeding ports. As a nonlinear design and validation instance, we present the nonlinear characterization up to 50 GHz of a PIN diode commonly used as a switch for reconfigurable devices in the microwave band. Nonlinear models are extracted through X-parameter measurements supported by accurate calibration and de-embedding procedures. Nonlinear switch models are validated by S-parameter measurements in the low power signal regime and by harmonic measurements in the large-signal regime and are further used to predict the measured nonlinearities of a reconfigurable antenna. These models have the desired particularity of being integrated straightforwardly in the internal multi-port method formulation, which is used and extended to account for the power induced on the switching elements. A new figure of merit for the design of reconfigurable antennas is introduced—the power margin, that is, the power difference between the fed port and the switching elements, which combined with the nonlinear load models directly translates into nonlinearities and power-efficiency-related metrics. Therefore, beyond traditional antenna aspects such as port match, gain, and beam orientation, switch power criteria are included in the design methodology. Guidelines for the design of reconfigurable antennas and parasitic layers of minimum nonlinearity are provided as well as the inherent trade-offs. A particular antenna design suitable for 5G communications in the 3.5 GHz band is presented according to these guidelines, in which the specific switching states for a set of target performance metrics are obtained via a balancing of the available figures of merit with multi-objective separation criteria, which enables good control of the various design trade-offs. Average Error Vector Magnitude (EVM) and power efficiency improvement of 12 and 6 dB, respectively, are obtained with the application of this design approach. In summary, this paper introduces a new framework for the nonlinear modeling and design of reconfigurable antennas and provides a set of general-purpose tools applicable in cases beyond those used as examples and validation in this work. Additionally, the use of these models and guidelines is presented, demonstrating one of the most appealing advantages of the reconfigurable parasitic layer approach, their low nonlinearity. Full article
(This article belongs to the Special Issue Antenna Design for 5G and Beyond)
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20 pages, 1698 KiB  
Article
Qualitative Assessment of Effective Gamification Design Processes Using Motivators to Identify Game Mechanics
by Eva Villegas, David Fonseca, Enric Peña, Paula Bonet and Sara Fernández-Guinea
Sensors 2021, 21(7), 2556; https://doi.org/10.3390/s21072556 - 6 Apr 2021
Cited by 12 | Viewed by 4976
Abstract
This research focuses on the study and qualitative assessment of the relationships between motivators and game mechanics per the ratings of expert gamification consultants. By taking this approach, it is intended that during the design phase of a gamified system, decisions can be [...] Read more.
This research focuses on the study and qualitative assessment of the relationships between motivators and game mechanics per the ratings of expert gamification consultants. By taking this approach, it is intended that during the design phase of a gamified system, decisions can be made about the design of the system based on the motivators of each of the profiles. These motivators can be determined from the information provided by the potential players themselves. The research presented starts from a previous analysis in which, based on the three most used gamification frameworks and through a card sorting technique that allows the user to organize and classify the content, a set of mechanics are determined. In the present study, each of the mechanics is analyzed, and a more precise motive is decided. As a result, a higher level of personalization is achieved and, consequently, approximates a higher level of gamification effectiveness. The main conclusions are implemented in the development of the Game4City 3.0 project, which addresses gamified and interactive strategies to visualize urban environments in 3D at an educational and social level. Full article
(This article belongs to the Special Issue Pervasive Mobile-Based Games, AR/VR and Sensors)
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19 pages, 2872 KiB  
Article
Label-Free Protein Detection by Micro-Acoustic Biosensor Coupled with Electrical Field Sorting. Theoretical Study in Urine Models
by Nikolay Mukhin, Georgii Konoplev, Aleksandr Oseev, Marc-Peter Schmidt, Oksana Stepanova, Andrey Kozyrev, Alexander Dmitriev and Soeren Hirsch
Sensors 2021, 21(7), 2555; https://doi.org/10.3390/s21072555 - 6 Apr 2021
Cited by 6 | Viewed by 4208
Abstract
Diagnostic devices for point-of-care (POC) urine analysis (urinalysis) based on microfluidic technology have been actively developing for several decades as an alternative to laboratory based biochemical assays. Urine proteins (albumin, immunoglobulins, uromodulin, haemoglobin etc.) are important biomarkers of various pathological conditions and should [...] Read more.
Diagnostic devices for point-of-care (POC) urine analysis (urinalysis) based on microfluidic technology have been actively developing for several decades as an alternative to laboratory based biochemical assays. Urine proteins (albumin, immunoglobulins, uromodulin, haemoglobin etc.) are important biomarkers of various pathological conditions and should be selectively detected by urinalysis sensors. The challenge is a determination of different oligomeric forms of the same protein, e.g., uromodulin, which have similar bio-chemical affinity but different physical properties. For the selective detection of different types of proteins, we propose to use a shear bulk acoustic resonator sensor with an additional electrode on the upper part of the bioliquid-filled channel for protein electric field manipulation. It causes modulation of the protein concentration over time in the near-surface region of the acoustic sensor, that allows to distinguish proteins based on their differences in diffusion coefficients (or sizes) and zeta-potentials. Moreover, in order to improve the sensitivity to density, we propose to use structured sensor interface. A numerical study of this approach for the detection of proteins was carried out using the example of albumin, immunoglobulin, and oligomeric forms of uromodulin in model urine solutions. In this contribution we prove the proposed concept with numerical studies for the detection of albumin, immunoglobulin, and oligomeric forms of uromodulin in urine models. Full article
(This article belongs to the Collection Enabling Technologies for Biosensors)
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44 pages, 8038 KiB  
Review
The Key Role of Active Sites in the Development of Selective Metal Oxide Sensor Materials
by Artem Marikutsa, Marina Rumyantseva, Elizaveta A. Konstantinova and Alexander Gaskov
Sensors 2021, 21(7), 2554; https://doi.org/10.3390/s21072554 - 6 Apr 2021
Cited by 89 | Viewed by 6956
Abstract
Development of sensor materials based on metal oxide semiconductors (MOS) for selective gas sensors is challenging for the tasks of air quality monitoring, early fire detection, gas leaks search, breath analysis, etc. An extensive range of sensor materials has been elaborated, but no [...] Read more.
Development of sensor materials based on metal oxide semiconductors (MOS) for selective gas sensors is challenging for the tasks of air quality monitoring, early fire detection, gas leaks search, breath analysis, etc. An extensive range of sensor materials has been elaborated, but no consistent guidelines can be found for choosing a material composition targeting the selective detection of specific gases. Fundamental relations between material composition and sensing behavior have not been unambiguously established. In the present review, we summarize our recent works on the research of active sites and gas sensing behavior of n-type semiconductor metal oxides with different composition (simple oxides ZnO, In2O3, SnO2, WO3; mixed-metal oxides BaSnO3, Bi2WO6), and functionalized by catalytic noble metals (Ru, Pd, Au). The materials were variously characterized. The composition, metal-oxygen bonding, microstructure, active sites, sensing behavior, and interaction routes with gases (CO, NH3, SO2, VOC, NO2) were examined. The key role of active sites in determining the selectivity of sensor materials is substantiated. It was shown that the metal-oxygen bond energy of the MOS correlates with the surface acidity and the concentration of surface oxygen species and oxygen vacancies, which control the adsorption and redox conversion of analyte gas molecules. The effects of cations in mixed-metal oxides on the sensitivity and selectivity of BaSnO3 and Bi2WO6 to SO2 and VOCs, respectively, are rationalized. The determining role of catalytic noble metals in oxidation of reducing analyte gases and the impact of acid sites of MOS to gas adsorption are demonstrated. Full article
(This article belongs to the Special Issue Biennial State-of-the-Art Sensors Technology in Russia 2020-2021)
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27 pages, 18630 KiB  
Review
3D Sensors for Sewer Inspection: A Quantitative Review and Analysis
by Chris H. Bahnsen, Anders S. Johansen, Mark P. Philipsen, Jesper W. Henriksen, Kamal Nasrollahi and Thomas B. Moeslund
Sensors 2021, 21(7), 2553; https://doi.org/10.3390/s21072553 - 6 Apr 2021
Cited by 29 | Viewed by 6019
Abstract
Automating inspection of critical infrastructure such as sewer systems will help utilities optimize maintenance and replacement schedules. The current inspection process consists of manual reviews of video as an operator controls a sewer inspection vehicle remotely. The process is slow, labor-intensive, and expensive [...] Read more.
Automating inspection of critical infrastructure such as sewer systems will help utilities optimize maintenance and replacement schedules. The current inspection process consists of manual reviews of video as an operator controls a sewer inspection vehicle remotely. The process is slow, labor-intensive, and expensive and presents a huge potential for automation. With this work, we address a central component of the next generation of robotic inspection of sewers, namely the choice of 3D sensing technology. We investigate three prominent techniques for 3D vision: passive stereo, active stereo, and time-of-flight (ToF). The Realsense D435 camera is chosen as the representative of the first two techniques wheres the PMD CamBoard pico flexx represents ToF. The 3D reconstruction performance of the sensors is assessed in both a laboratory setup and in an outdoor above-ground setup. The acquired point clouds from the sensors are compared with reference 3D models using the cloud-to-mesh metric. The reconstruction performance of the sensors is tested with respect to different illuminance levels and different levels of water in the pipes. The results of the tests show that the ToF-based point cloud from the pico flexx is superior to the output of the active and passive stereo cameras. Full article
(This article belongs to the Special Issue Computer Vision for 3D Perception and Applications)
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10 pages, 22287 KiB  
Communication
Leptospira interrogans Outer Membrane Protein-Based Nanohybrid Sensor for the Diagnosis of Leptospirosis
by Vivek Verma, Deepak Kala, Shagun Gupta, Harsh Kumar, Ankur Kaushal, Kamil Kuča, Natália Cruz-Martins and Dinesh Kumar
Sensors 2021, 21(7), 2552; https://doi.org/10.3390/s21072552 - 6 Apr 2021
Cited by 20 | Viewed by 3957
Abstract
Leptospirosis is an underestimated tropical disease caused by the pathogenic Leptospira species and responsible for several serious health problems. Here, we aimed to develop an ultrasensitive DNA biosensor for the rapid and on-site detection of the Loa22 gene of Leptospira interrogans using a [...] Read more.
Leptospirosis is an underestimated tropical disease caused by the pathogenic Leptospira species and responsible for several serious health problems. Here, we aimed to develop an ultrasensitive DNA biosensor for the rapid and on-site detection of the Loa22 gene of Leptospira interrogans using a gold nanoparticle–carbon nanofiber composite (AuN/CNF)-based screen-printed electrode. Cyclic voltammetry and electrochemical impedance were performed for electrochemical analysis. The sensitivity of the sensor was 5431.74 μA/cm2/ng with a LOD (detection limit) of 0.0077 ng/μL using cyclic voltammetry. The developed DNA biosensor was found highly specific to the Loa22 gene of L. interrogans, with a storage stability at 4 °C for 180 days and a 6% loss of the initial response. This DNA-based sensor only takes 30 min for rapid detection of the pathogen, with a higher specificity and sensitivity. The promising results obtained suggest the application of the developed sensor as a point of care device for the diagnosis of leptospirosis. Full article
(This article belongs to the Special Issue Screen-Printed Electrochemical Sensors and Their Applications)
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17 pages, 4791 KiB  
Article
An 18.8–33.9 GHz, 2.26 mW Current-Reuse Injection-Locked Frequency Divider for Radar Sensor Applications
by Kwang-Il Oh, Goo-Han Ko, Jeong-Geun Kim and Donghyun Baek
Sensors 2021, 21(7), 2551; https://doi.org/10.3390/s21072551 - 6 Apr 2021
Cited by 6 | Viewed by 2826
Abstract
An 18.8–33.9 GHz, 2.26 mW current-reuse (CR) injection-locked frequency divider (ILFD) for radar sensor applications is presented in this paper. A fourth-order resonator is designed using a transformer with a distributed inductor for wideband operating of the ILFD. The CR core is employed [...] Read more.
An 18.8–33.9 GHz, 2.26 mW current-reuse (CR) injection-locked frequency divider (ILFD) for radar sensor applications is presented in this paper. A fourth-order resonator is designed using a transformer with a distributed inductor for wideband operating of the ILFD. The CR core is employed to reduce the power consumption compared to conventional cross-coupled pair ILFDs. The targeted input center frequency is 24 GHz for radar application. The self-oscillated frequency of the proposed CR-ILFD is 14.08 GHz. The input frequency locking range is from 18.8 to 33.8 GHz (57%) at an injection power of 0 dBm without a capacitor bank or varactors. The proposed CR-ILFD consumes 2.26 mW of power from a 1 V supply voltage. The entire die size is 0.75 mm × 0.45 mm. This CR-ILFD is implemented in a 65 nm complementary metal-oxide semiconductor (CMOS) technology. Full article
(This article belongs to the Special Issue Advanced CMOS Integrated Circuit Design and Application)
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13 pages, 296 KiB  
Article
Beam Allocation and Power Optimization for Energy-Efficiency in Multiuser mmWave Massive MIMO System
by Saidiwaerdi Maimaiti, Gang Chuai, Weidong Gao and Jinxi Zhang
Sensors 2021, 21(7), 2550; https://doi.org/10.3390/s21072550 - 6 Apr 2021
Cited by 3 | Viewed by 2310
Abstract
This paper studies beam allocation and power optimization scheme to decrease the hardware cost and downlink power consumption of a multiuser millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) system. Our target is to improve energy efficiency (EE) and decrease power consumption without obvious [...] Read more.
This paper studies beam allocation and power optimization scheme to decrease the hardware cost and downlink power consumption of a multiuser millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) system. Our target is to improve energy efficiency (EE) and decrease power consumption without obvious system performance loss. To this end, we propose a beam allocation and power optimization scheme. First, the problem of beam allocation and power optimization is formulated as a multivariate mixed-integer non-linear programming problem. Second, due to the non-convexity of this problem, we decompose it into two sub-problems which are beam allocation and power optimization. Finally, the beam allocation problem is solved by using a convex optimization technique. We solve the power optimization problem in two steps. First, the non-convex problem is converted into a convex problem by using a quadratic transformation scheme. The second step implements Lagrange dual and sub-gradient methods to solve the optimization problem. Performance analysis and simulation results show that the proposed algorithm performs almost identical to the exhaustive search (ES) method, while the greedy beam allocation and suboptimal beam allocation methods are far from the ES. Furthermore, experiment results demonstrated that our proposed algorithm outperforms the compared the greedy beam allocation method and the suboptimal beam allocation scheme in terms of average service ratio. Full article
(This article belongs to the Special Issue Energy-Efficient Resource Allocation for beyond 5G and IoT Systems)
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10 pages, 3617 KiB  
Communication
Use of the Composite Properties of a Microwave Resonator to Enhance the Sensitivity of a Honey Moisture Sensor
by José R. Reyes-Ayona, Eloisa Gallegos-Arellano and Juan M. Sierra-Hernández
Sensors 2021, 21(7), 2549; https://doi.org/10.3390/s21072549 - 6 Apr 2021
Cited by 1 | Viewed by 2178
Abstract
A moisture sensor based on a composite resonator is used to measure different honey samples, which include imitation honey. The sensor changes its frequency response in accordance with the dielectric permittivity that it detects in the measured samples. Although reflectometry sensors have been [...] Read more.
A moisture sensor based on a composite resonator is used to measure different honey samples, which include imitation honey. The sensor changes its frequency response in accordance with the dielectric permittivity that it detects in the measured samples. Although reflectometry sensors have been used to measure the percentage of moisture in honey for almost a century, counterfeiters have achieved that their apocryphal product is capable of deceiving these kinds of sensors. Metamaterial features of the composite resonators are expected to improve their response when detecting lossy samples such as organic samples. It is also sought that these sensors manage to detect small differences not only in the real parts of the dielectric permitivities of samples but also in their imaginary parts, and, thus, the sensors are able to discern between real honey and slightly altered honey. Effectively, not only was it possible to improve the response of the sensors by using lossy samples but it was also possible to identify counterfeit honey. Full article
(This article belongs to the Special Issue Biomedical Microwave Sensors for Point-of-Care Applications)
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19 pages, 3962 KiB  
Article
Estimation of Tissue Attenuation from Ultrasonic B-Mode Images—Spectral-Log-Difference and Method-of-Moments Algorithms Compared
by Dinah Maria Brandner, Xiran Cai, Josquin Foiret, Katherine W. Ferrara and Bernhard G. Zagar
Sensors 2021, 21(7), 2548; https://doi.org/10.3390/s21072548 - 5 Apr 2021
Cited by 13 | Viewed by 4219
Abstract
We report on results from the comparison of two algorithms designed to estimate the attenuation coefficient from ultrasonic B-mode scans obtained from a numerical phantom simulating an ultrasound breast scan. It is well documented that this parameter significantly diverges between normal tissue and [...] Read more.
We report on results from the comparison of two algorithms designed to estimate the attenuation coefficient from ultrasonic B-mode scans obtained from a numerical phantom simulating an ultrasound breast scan. It is well documented that this parameter significantly diverges between normal tissue and malignant lesions. To improve the diagnostic accuracy it is of great importance to devise and test algorithms that facilitate the accurate, low variance and spatially resolved estimation of the tissue’s attenuation properties. A numerical phantom is realized using k-Wave, which is an open source Matlab toolbox for the time-domain simulation of acoustic wave fields that facilitates both linear and nonlinear wave propagation in homogeneous and heterogeneous tissue, as compared to strictly linear ultrasound simulation tools like Field II. k-Wave allows to simulate arbitrary distributions, resolved down to single voxel sizes, of parameters including the speed of sound, mass density, scattering strength and to include power law acoustic absorption necessary for simulation tasks in medical diagnostic ultrasound. We analyze the properties and the attainable accuracy of both the spectral-log-difference technique, and a statistical moments based approach and compare the results to known reference values from the sound field simulation. Full article
(This article belongs to the Special Issue Selected Papers from 6th International Conference on Sensors and Electronic Instrumentation Advances (SEIA’ 2020))
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23 pages, 4617 KiB  
Article
Multi-Sensor Fault Detection, Identification, Isolation and Health Forecasting for Autonomous Vehicles
by Saeid Safavi, Mohammad Amin Safavi, Hossein Hamid and Saber Fallah
Sensors 2021, 21(7), 2547; https://doi.org/10.3390/s21072547 - 5 Apr 2021
Cited by 54 | Viewed by 10389
Abstract
The primary focus of autonomous driving research is to improve driving accuracy and reliability. While great progress has been made, state-of-the-art algorithms still fail at times and some of these failures are due to the faults in sensors. Such failures may have fatal [...] Read more.
The primary focus of autonomous driving research is to improve driving accuracy and reliability. While great progress has been made, state-of-the-art algorithms still fail at times and some of these failures are due to the faults in sensors. Such failures may have fatal consequences. It therefore is important that automated cars foresee problems ahead as early as possible. By using real-world data and artificial injection of different types of sensor faults to the healthy signals, data models can be trained using machine learning techniques. This paper proposes a novel fault detection, isolation, identification and prediction (based on detection) architecture for multi-fault in multi-sensor systems, such as autonomous vehicles.Our detection, identification and isolation platform uses two distinct and efficient deep neural network architectures and obtained very impressive performance. Utilizing the sensor fault detection system’s output, we then introduce our health index measure and use it to train the health index forecasting network. Full article
(This article belongs to the Special Issue Artificial Intelligence and Internet of Things in Autonomous Vehicles)
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16 pages, 7467 KiB  
Article
Non-Destructive and Quantitative Evaluation of Rebar Corrosion by a Vibro-Doppler Radar Method
by Takashi Miwa
Sensors 2021, 21(7), 2546; https://doi.org/10.3390/s21072546 - 5 Apr 2021
Cited by 11 | Viewed by 3653
Abstract
It is well known that evaluation of rebar corrosion is important for the maintenance of reinforced concrete structures, but, it is difficult to simply, quickly and quantitatively evaluate the amount of corrosion of rebars embedded in concrete by conventional non-destructive evaluation (NDE) methods [...] Read more.
It is well known that evaluation of rebar corrosion is important for the maintenance of reinforced concrete structures, but, it is difficult to simply, quickly and quantitatively evaluate the amount of corrosion of rebars embedded in concrete by conventional non-destructive evaluation (NDE) methods such as electrical, electromagnetic and mechanical method. This paper proposes a vibro-Doppler radar (VDR) measurement method to quantitatively evaluate rebar corrosion by measuring the vibration ability of the rebar forcibly vibrated in concrete by an excitation coil. It is experimentally demonstrated in RC test pieces that the rebar vibration displacement obtained by developed VDR method is valid and is less affected by the moisture in the concrete. In addition, simultaneous monitoring of the rebar vibration displacement of the test pieces is performed through an electrolytic corrosion test and the measured vibration displacement is compared to the rebar corrosion loss evaluated. As the results, it is cleared that the rebar vibration displacement starts to increase from slightly before the occurrences of corrosion crack on the concrete surface as the corrosion loss increases. It is also shown that the rebar vibration displacement becomes 4 times higher than that in initial condition at the rebar corrosion loss of 250 mg/cm2. This implies that the VDR has potential to nondestructively and quantitatively evaluate rebar corrosion in concrete. Full article
(This article belongs to the Special Issue Sensing Advancement and Health Monitoring of Transport Structures)
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17 pages, 21229 KiB  
Article
A Compensation Method for Nonlinear Vibration of Silicon-Micro Resonant Sensor
by Yan Li, Hao Li, Yifeng Xiao, Le Cao and Zhan-She Guo
Sensors 2021, 21(7), 2545; https://doi.org/10.3390/s21072545 - 5 Apr 2021
Cited by 9 | Viewed by 3016
Abstract
A compensation method for nonlinear vibration of a silicon micro resonant sensor is proposed and evaluated to be effective through simulation and experimental analysis. Firstly, the parameter characterization model of the silicon micro resonant sensor is established, which presents significant nonlinearity because of [...] Read more.
A compensation method for nonlinear vibration of a silicon micro resonant sensor is proposed and evaluated to be effective through simulation and experimental analysis. Firstly, the parameter characterization model of the silicon micro resonant sensor is established, which presents significant nonlinearity because of the nonlinear vibration of the resonant beam. A verification circuit is devised to imitate the nonlinear behavior of the model by matching the simulation measurement error of the frequency offset produced by the circuit block with the theoretical counterparts obtained from the model. Secondly, the principle of measurement error compensation is studied, and the compensation method dealing with nonlinear characteristics of the resonant beam is proposed by introducing a compensation beam and corresponding differential operations. The measurement error, compensation rate, and measurement residual between the two scenarios that use single beam and double beams, respectively, are derived and are compared with their simulation and experimental counterparts. The results coincide with the predicted trend, which verifies the effectiveness of the compensation method. Full article
(This article belongs to the Special Issue MEMS Actuators and Sensors 2022)
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20 pages, 851 KiB  
Article
Performance Study of Distance-Weighting Approach with Loopy Sum-Product Algorithm for Multi-Object Tracking in Clutter
by Pranav U. Damale, Edwin K. P. Chong and Tian J. Ma
Sensors 2021, 21(7), 2544; https://doi.org/10.3390/s21072544 - 5 Apr 2021
Cited by 3 | Viewed by 2581
Abstract
In this paper, we explore the performance of the distance-weighting probabilistic data association (DWPDA) approach in conjunction with the loopy sum-product algorithm (LSPA) for tracking multiple objects in clutter. First, we discuss the problem of data association (DA), which is to infer the [...] Read more.
In this paper, we explore the performance of the distance-weighting probabilistic data association (DWPDA) approach in conjunction with the loopy sum-product algorithm (LSPA) for tracking multiple objects in clutter. First, we discuss the problem of data association (DA), which is to infer the correspondence between targets and measurements. DA plays an important role when tracking multiple targets using measurements of uncertain origin. Second, we describe three methods of data association: probabilistic data association (PDA), joint probabilistic data association (JPDA), and LSPA. We then apply these three DA methods for tracking multiple crossing targets in cluttered environments, e.g., radar detection with false alarms and missed detections. We are interested in two performance metrics: tracking accuracy and computation time. LSPA is known to be superior to PDA in terms of the former and to dominate JPDA in terms of the latter. Last, we consider an additional DA method that is a modification of PDA by incorporating a weighting scheme based on distances between position estimates and measurements. This distance-weighting approach, when combined with PDA, has been shown to enhance the tracking accuracy of PDA without significant change in the computation burden. Since PDA constitutes a crucial building block of LSPA, we hypothesize that DWPDA, when integrated with LSPA, would perform better under the two performance metrics above. Contrary to expectations, the distance-weighting approach does not enhance the performance of LSPA, whether in terms of tracking accuracy or computation time. Full article
(This article belongs to the Special Issue Multi-Sensor Fusion for Object Detection and Tracking)
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