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Sensors, Volume 23, Issue 2 (January-2 2023) – 492 articles

Cover Story (view full-size image): There is a growing desire to monitor and control harmful substances that impact upon our quality of life. Thermal conductivity gas sensors offer several advantages that include high reproducibility, stability, low cost, low power consumption, simple construction, fast response time, long lifetime, and wide dynamic range and are thus rapidly gaining renewed interest. This timely review focuses on the state of the art in thermal conductivity sensors; it contains a general introduction, theory of operation, interface electronics, use in commercial applications, and recent research developments. In addition, both steady‐state and transient methods of operation are discussed with their relative advantages and disadvantages presented. Finally, some recent innovations in thermal conductivity gas sensing are explored. View this paper
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17 pages, 9104 KiB  
Article
Multirotor Motor Failure Detection with Piezo Sensor
by Leszek Ambroziak, Daniel Ołdziej and Andrzej Koszewnik
Sensors 2023, 23(2), 1048; https://doi.org/10.3390/s23021048 - 16 Jan 2023
Cited by 6 | Viewed by 2464
Abstract
Failure detection of Unmanned Aerial Vehicle (UAV) motors and propulsion systems is the most important step in the implementation of active fault-tolerant control systems. This will increase the reliability of unmanned systems and increase the level of safety, especially in civil and commercial [...] Read more.
Failure detection of Unmanned Aerial Vehicle (UAV) motors and propulsion systems is the most important step in the implementation of active fault-tolerant control systems. This will increase the reliability of unmanned systems and increase the level of safety, especially in civil and commercial applications. The following paper presents a method of motor failure detection in the multirotor UAV using piezo bars. The results of a real flight, in which the failure of the propulsion system caused the crash of a hybrid VTOL UAV, were presented and analyzed. The conclusions drawn from this flight led to the development of a lightweight, simple and reliable sensor that can detect a failure of the UAV propulsion system. The article presents the outcomes of laboratory tests concerning measurements made with a piezo sensor. An extensive analysis of the obtained results of vibrations recorded on a flying platform arm with a propulsion system is presented, and a methodology for using this type of data to detect failures is proposed. The article presents the possibility of using a piezoelectric sensor to record vibrations on the basis of which it is possible to detect a failure of the UAV propulsion system. Full article
(This article belongs to the Special Issue Smart Sensing and Artificial Intelligence for Civil Infrastructure Monitoring and Management)
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30 pages, 6316 KiB  
Article
OpenCare5G: O-RAN in Private Network for Digital Health Applications
by Wagner de Oliveira, José Olimpio Rodrigues Batista, Jr., Tiago Novais, Silvio Toshiyuki Takashima, Leonardo Roccon Stange, Moacyr Martucci, Jr., Carlos Eduardo Cugnasca and Graça Bressan
Sensors 2023, 23(2), 1047; https://doi.org/10.3390/s23021047 - 16 Jan 2023
Cited by 4 | Viewed by 4254
Abstract
Digital Health is a new way for medicine to work together with computer engineering and ICT to carry out tests and obtain reliable information about the health status of citizens in the most remote places in Brazil in near-real time, applying new technologies [...] Read more.
Digital Health is a new way for medicine to work together with computer engineering and ICT to carry out tests and obtain reliable information about the health status of citizens in the most remote places in Brazil in near-real time, applying new technologies and digital tools in the process. InovaHC is the technological innovation core of the Clinics Hospital of the Faculty of Medicine of the University of São Paulo (HCFMUSP). It is the first national medical institution to seek new opportunities offered by 5G technology and test its application in the first private network for Digital Health in the largest hospital complex in Latin America through the OpenCare5G Project. This project uses an Open RAN concept and network disaggregation with lower costs than the traditional concept used by the telecommunications industry. The technological project connected to the 5G network was divided into two phases for proof-of-concept testing: the first with an initial focus on carrying out examinations with portable ultrasound equipment in different locations at HCFMUSP, and the second focusing on carrying out remote examinations with health professionals in other states of Brazil, who will be working in remote areas in other states with little or no ICT infrastructure together with a doctor analyzing exams in real time at HCFMUSP in São Paulo. The objective of the project is to evaluate the connectivity and capacity of the 5G private network in these the proof-of-concept tests for transmitting the volume of data from remote exams with higher speed and lower latency. We are in the first phase of the proof of concept testing to achieve the expected success. This project is a catalyst for innovation in health, connecting resources and entrepreneurs to generate solutions for the innovation ecosystem of organizations. It is coordinated by Deloitte with the participation of the Escola Politécnica da USP (The School of Engineering—University of São Paulo), Airspan, Itaú Bank, Siemens Healthineers, NEC, Telecom Infra Projet, ABDI and IDB. The use of 5G Open RAN technology in public health is concluded to be of extreme social, economic, and fundamental importance for HCFMUSP, citizens, and the development of health research to promote great positive impacts ranging from attracting investment in the country to improving the quality of patient care. Full article
(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)
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16 pages, 915 KiB  
Article
Condition Monitoring of Induction Machines: Quantitative Analysis and Comparison
by Michele Sintoni, Elena Macrelli, Alberto Bellini and Claudio Bianchini
Sensors 2023, 23(2), 1046; https://doi.org/10.3390/s23021046 - 16 Jan 2023
Cited by 3 | Viewed by 1694
Abstract
In this paper, a diagnostic procedure for rotor bar faults in induction motors is presented, based on the Hilbert and discrete wavelet transforms. The method is compared with other procedures with the same data, which are based on time–frequency analysis, frequency analysis and [...] Read more.
In this paper, a diagnostic procedure for rotor bar faults in induction motors is presented, based on the Hilbert and discrete wavelet transforms. The method is compared with other procedures with the same data, which are based on time–frequency analysis, frequency analysis and time domain. The results show that this method improves the rotor fault detection in transient conditions. Variable speed drive applications are common in industry. However, traditional condition monitoring methods fail in time-varying conditions or with load oscillations. This method is based on the combined use of the Hilbert and discrete wavelet transforms, which compute the energy in a bandwidth corresponding to the maximum fault signature. Theoretical analysis, numerical simulation and experiments are presented, which confirm the enhanced performance of the proposed method with respect to prior solutions, especially in time-varying conditions. The comparison is based on quantitative analysis that helps in choosing the optimal trade-off between performance and (computational) cost. Full article
(This article belongs to the Special Issue Sensor Applications in Fault Diagnosis and Monitoring of Electrical Machines II)
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16 pages, 930 KiB  
Article
Turntable IMU Calibration Algorithm Based on the Fourier Transform Technique
by Yury Bolotin and Vladimir Savin
Sensors 2023, 23(2), 1045; https://doi.org/10.3390/s23021045 - 16 Jan 2023
Cited by 2 | Viewed by 2363
Abstract
The paper suggests a new approach to calibration of a micromechanical inertial measurement unit. The data are collected on a simple rotating turntable with horizontal (or close to) rotation axis. For such a turntable, an electric screwdriver with fairly low rotation rate can [...] Read more.
The paper suggests a new approach to calibration of a micromechanical inertial measurement unit. The data are collected on a simple rotating turntable with horizontal (or close to) rotation axis. For such a turntable, an electric screwdriver with fairly low rotation rate can be used. The algorithm is based on the Fourier transform applied to the rotation experimental data, implemented as FFT. The frequencies and amplitudes of the spectral peaks are calculated and collected in a small set of data, and calibration is done explicitly with these data. Calibration of an accelerometer triad and choosing the IMU coordinate frame are reduced to approximating the collected data with an ellipsoid in three dimensions. With rotation frequency calculated as the peak frequency of accelerometer readings, calibration of the gyros is a straightforward linear least square problem. The algorithm is purely algebraic, requires no iterations and no initial guess on the parameters, and thus encounters no convergence problems. The algorithm was tested both with simulated and experimental data, with some promising results. Full article
(This article belongs to the Special Issue Advances of Navigation, Positioning, Monitoring and Predicting Based on Inertial Sensors)
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18 pages, 6075 KiB  
Article
Rapid Design Optimization and Calibration of Microwave Sensors Based on Equivalent Complementary Resonators for High Sensitivity and Low Fabrication Tolerance
by Tanveerul Haq and Slawomir Koziel
Sensors 2023, 23(2), 1044; https://doi.org/10.3390/s23021044 - 16 Jan 2023
Cited by 11 | Viewed by 1918
Abstract
This paper presents the design, optimization, and calibration of multivariable resonators for microwave dielectric sensors. An optimization technique for the circular complementary split ring resonator (CC-SRR) and square complementary split ring resonator (SC-SRR) is presented to achieve the required transmission response in a [...] Read more.
This paper presents the design, optimization, and calibration of multivariable resonators for microwave dielectric sensors. An optimization technique for the circular complementary split ring resonator (CC-SRR) and square complementary split ring resonator (SC-SRR) is presented to achieve the required transmission response in a precise manner. The optimized resonators are manufactured using a standard photolithographic technique and measured for fabrication tolerance. The fabricated sensor is presented for the high-resolution characterization of dielectric substrates and oil samples. A three-dimensional dielectric container is attached to the sensor and acts as a pool for the sample under test (SUT). In the presented technique, the dielectric substrates and oil samples can interact directly with the electromagnetic (EM) field emitted from the resonator. For the sake of sensor calibration, a relation between the relative permittivity of the dielectric samples and the resonant frequency of the sensor is established in the form of an inverse regression model. Comparisons with state-of-the-art sensors indicate the superiority of the presented design in terms of oil characterization reliability. The significant technical contributions of this work include the employment of the rigorous optimization of geometry parameters of the sensor, leading to its superior performance, and the development and application of the inverse-model-based calibration procedure. Full article
(This article belongs to the Special Issue Microwave Sensors for Industrial Applications)
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18 pages, 3653 KiB  
Article
Deep Learning-Based Adaptive Compression and Anomaly Detection for Smart B5G Use Cases Operation
by Ahmad El Sayed, Marc Ruiz, Hassan Harb and Luis Velasco
Sensors 2023, 23(2), 1043; https://doi.org/10.3390/s23021043 - 16 Jan 2023
Cited by 3 | Viewed by 1888
Abstract
The evolution towards next-generation Beyond 5G (B5G) networks will require not only innovation in transport technologies but also the adoption of smarter, more efficient operations of the use cases that are foreseen to be the high consumers of network resources in the next [...] Read more.
The evolution towards next-generation Beyond 5G (B5G) networks will require not only innovation in transport technologies but also the adoption of smarter, more efficient operations of the use cases that are foreseen to be the high consumers of network resources in the next decades. Among different B5G use cases, the Digital Twin (DT) has been identified as a key high bandwidth-demanding use case. The creation and operation of a DT require the continuous collection of an enormous and widely distributed amount of sensor telemetry data which can overwhelm the transport layer. Therefore, the reduction in such transported telemetry data is an essential objective of smart use case operation. Moreover, deep telemetry data analysis, i.e., anomaly detection, can be executed in a hierarchical way to reduce the processing needed to perform such analysis in a centralized way. In this paper, we propose a smart management system consisting of a hierarchical architecture for telemetry sensor data analysis using deep autoencoders (AEs). The system contains AE-based methods for the adaptive compression of telemetry time series data using pools of AEs (called AAC), as well as for anomaly detection in single (called SS-AD) and multiple (called MS-AGD) sensor streams. Numerical results using experimental telemetry data show compression ratios of up to 64% with reconstruction errors of less than 1%, clearly improving upon the benchmark state-of-the-art methods. In addition, fast and accurate anomaly detection is demonstrated for both single and multiple-sensor scenarios. Finally, a great reduction in transport network capacity resources of 50% and more is obtained by smart use case operation for distributed DT scenarios. Full article
(This article belongs to the Special Issue Towards Next Generation beyond 5G (B5G) Networks)
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12 pages, 3410 KiB  
Article
Eddy Current Testing of Conductive Coatings Using a Pot-Core Sensor
by Grzegorz Tytko
Sensors 2023, 23(2), 1042; https://doi.org/10.3390/s23021042 - 16 Jan 2023
Cited by 4 | Viewed by 1628
Abstract
Conductors consisting of thin layers are commonly used in many industries as protective, insulating or thermal barrier coatings (TBC). Nondestructive testing of these types of structures allows one to determine their dimensions and technical condition, while also detecting defects, which significantly reduces the [...] Read more.
Conductors consisting of thin layers are commonly used in many industries as protective, insulating or thermal barrier coatings (TBC). Nondestructive testing of these types of structures allows one to determine their dimensions and technical condition, while also detecting defects, which significantly reduces the risk of failures and accidents. This work presents an eddy current system for testing thin layers and coatings, which has never been presented before. It consists of an analytical model and a pot-core sensor. The analytical model was derived through the employment of the truncated region eigenfunction expansion (TREE) method. The final formulas for the sensor impedance have been presented in a closed form and implemented in Matlab. The results of the calculations of the pot-core sensor impedance for thin layers with a thickness above 0.1 mm were compared with the measurement results. The calculations made for the TBC were verified with a numerical model created using the finite element method (FEM) in Comsol Multiphysics. In all the cases, the error in determining changes in the components of the pot-core sensor impedance was less than 4%. At the same time, it was shown that the sensitivity of the applied pot-core sensor in the case of thin-layer testing is much higher than the sensitivity of the air-core sensor and the I-core sensor. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)
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12 pages, 4491 KiB  
Article
Improved Bidirectional RRT* Algorithm for Robot Path Planning
by Peng Xin, Xiaomin Wang, Xiaoli Liu, Yanhui Wang, Zhibo Zhai and Xiqing Ma
Sensors 2023, 23(2), 1041; https://doi.org/10.3390/s23021041 - 16 Jan 2023
Cited by 7 | Viewed by 3226
Abstract
In order to address the shortcomings of the traditional bidirectional RRT* algorithm, such as its high degree of randomness, low search efficiency, and the many inflection points in the planned path, we institute improvements in the following directions. Firstly, to address the problem [...] Read more.
In order to address the shortcomings of the traditional bidirectional RRT* algorithm, such as its high degree of randomness, low search efficiency, and the many inflection points in the planned path, we institute improvements in the following directions. Firstly, to address the problem of the high degree of randomness in the process of random tree expansion, the expansion direction of the random tree growing at the starting point is constrained by the improved artificial potential field method; thus, the random tree grows towards the target point. Secondly, the random tree sampling point grown at the target point is biased to the random number sampling point grown at the starting point. Finally, the path planned by the improved bidirectional RRT* algorithm is optimized by extracting key points. Simulation experiments show that compared with the traditional A*, the traditional RRT, and the traditional bidirectional RRT*, the improved bidirectional RRT* algorithm has a shorter path length, higher path-planning efficiency, and fewer inflection points. The optimized path is segmented using the dynamic window method according to the key points. The path planned by the fusion algorithm in a complex environment is smoother and allows for excellent avoidance of temporary obstacles. Full article
(This article belongs to the Topic Advances in Mobile Robotics Navigation)
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8 pages, 3370 KiB  
Communication
High-Efficiency Plasma Source Using a Magnetic Mirror Trap for Miniature-Ion Pumps
by Yuichi Kurashima, Taisei Motomura, Shinya Yanagimachi, Takashi Matsumae, Mitsuhiro Watanabe and Hideki Takagi
Sensors 2023, 23(2), 1040; https://doi.org/10.3390/s23021040 - 16 Jan 2023
Viewed by 1244
Abstract
In this study, we design a highly efficient plasma source using a magnetic mirror trap with two opposing permanent magnets for a miniature high-efficiency ion pump. First, we simulated the distribution of the magnetic field line formed by the proposed magnetic mirror configuration. [...] Read more.
In this study, we design a highly efficient plasma source using a magnetic mirror trap with two opposing permanent magnets for a miniature high-efficiency ion pump. First, we simulated the distribution of the magnetic field line formed by the proposed magnetic mirror configuration. By optimizing the distance between two opposing permanent magnets and size of these magnets, a magnetic mirror ratio value of 27 could be obtained, which is an electron confinement efficiency of over 90%. We also conducted an experiment on a high-efficiency discharge plasma source for a miniature ion pump using an optimized magnetic circuit. As a result, we revealed that the proposed magnetic circuit has a pronounced effect on plasma generation, particularly in the high-vacuum region. Full article
(This article belongs to the Section Physical Sensors)
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14 pages, 9399 KiB  
Article
Human Postures Recognition by Accelerometer Sensor and ML Architecture Integrated in Embedded Platforms: Benchmarking and Performance Evaluation
by Alessandro Leone, Gabriele Rescio, Andrea Caroppo, Pietro Siciliano and Andrea Manni
Sensors 2023, 23(2), 1039; https://doi.org/10.3390/s23021039 - 16 Jan 2023
Cited by 10 | Viewed by 3613
Abstract
Embedded hardware systems, such as wearable devices, are widely used for health status monitoring of ageing people to improve their well-being. In this context, it becomes increasingly important to develop portable, easy-to-use, compact, and energy-efficient hardware-software platforms, to enhance the level of usability [...] Read more.
Embedded hardware systems, such as wearable devices, are widely used for health status monitoring of ageing people to improve their well-being. In this context, it becomes increasingly important to develop portable, easy-to-use, compact, and energy-efficient hardware-software platforms, to enhance the level of usability and promote their deployment. With this purpose an automatic tri-axial accelerometer-based system for postural recognition has been developed, useful in detecting potential inappropriate behavioral habits for the elderly. Systems in the literature and on the market for this type of analysis mostly use personal computers with high computing resources, which are not easily portable and have high power consumption. To overcome these limitations, a real-time posture recognition Machine Learning algorithm was developed and optimized that could perform highly on platforms with low computational capacity and power consumption. The software was integrated and tested on two low-cost embedded platform (Raspberry Pi 4 and Odroid N2+). The experimentation stage was performed on various Machine Learning pre-trained classifiers using data of seven elderly users. The preliminary results showed an activity classification accuracy of about 98% for the four analyzed postures (Standing, Sitting, Bending, and Lying down), with similar accuracy and a computational load as the state-of-the-art classifiers running on personal computers. Full article
(This article belongs to the Special Issue Movement Biomechanics Applications of Wearable Inertial Sensors)
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14 pages, 5768 KiB  
Article
Research on Educational Robot System Based on Vision Processing
by Jianwei Zhao, Yutian Gu, Qifeng Hou and Zhiwei Zhang
Sensors 2023, 23(2), 1038; https://doi.org/10.3390/s23021038 - 16 Jan 2023
Cited by 1 | Viewed by 1386
Abstract
Aimed at the poor recognition effect of current educational robots on objects with complex shapes and colors and the single design of related experiments, this paper proposes a robot teaching instrument. The robot adopts a servo motor with an encoder, a drive, and [...] Read more.
Aimed at the poor recognition effect of current educational robots on objects with complex shapes and colors and the single design of related experiments, this paper proposes a robot teaching instrument. The robot adopts a servo motor with an encoder, a drive, and a variety of sensors to realize a motor current loop, speed loop, position loop, and closed-loop control functions. Three experimental schemes were designed: a PID adjustment experiment, a robot obstacle avoidance and object-grasping program writing experiment, and a complex object recognition experiment based on cascade classifiers. The robot is conducive to improving students’ self-initiative ability, deepening their understanding of PID closed-loop control, multi-sensor fusion, and deep learning knowledge. It can improve students’ programming ability, enabling them to effectively combine theory and practice, as well as to comprehensively apply professional knowledge. Full article
(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)
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4 pages, 173 KiB  
Editorial
Advanced Sensing and Safety Control for Connected and Automated Vehicles
by Chao Huang, Yafei Wang, Peng Hang, Zhiqiang Zuo and Bo Leng
Sensors 2023, 23(2), 1037; https://doi.org/10.3390/s23021037 - 16 Jan 2023
Viewed by 1448
Abstract
The connected and automated vehicle (CAV) is a promising technology, anticipated to enhance the safety and effectiveness of mobility [...] Full article
(This article belongs to the Special Issue Advanced Sensing and Safety Control for Connected and Automated Vehicles)
19 pages, 7924 KiB  
Article
Peukert’s Law-Based State-of-Charge Estimation for Primary Battery Powered Sensor Nodes
by Hongli Dai, Yu Xia, Jing Mao, Cheng Xu, Wei Liu and Shunren Hu
Sensors 2023, 23(2), 1036; https://doi.org/10.3390/s23021036 - 16 Jan 2023
Viewed by 1504
Abstract
Accurate state-of-charge (SOC) estimation is essential for maximizing the lifetime of battery-powered wireless sensor networks (WSNs). Lightweight estimation methods are widely used in WSNs due to their low measurement and computation requirements. However, accuracy of existing lightweight methods is not high, and their [...] Read more.
Accurate state-of-charge (SOC) estimation is essential for maximizing the lifetime of battery-powered wireless sensor networks (WSNs). Lightweight estimation methods are widely used in WSNs due to their low measurement and computation requirements. However, accuracy of existing lightweight methods is not high, and their adaptability to different batteries and working conditions is relatively poor. This paper proposes a lightweight SOC estimation method, which applies Peukert’s Law to estimate the effective capacity of the battery and then calculates the SOC by subtracting the cumulative current consumption from the estimated capacity. In order to evaluate the proposed method comprehensively, different primary batteries and working conditions (constant current, constant resistance, and emulated duty-cycle loads) are employed. Experimental results show that the proposed method is superior to existing methods for different batteries and working conditions, which mainly benefits from the ability of Peukert’s Law to better model the rate-capacity effect of the batteries. Full article
(This article belongs to the Section Sensor Networks)
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20 pages, 7475 KiB  
Article
Analysis of the Underwater Radiated Noise Generated by Hull Vibrations of the Ships
by Rodrigo F. Javier, Ramis Jaime, Poveda Pedro, Carbajo Jesus and Segovia Enrique
Sensors 2023, 23(2), 1035; https://doi.org/10.3390/s23021035 - 16 Jan 2023
Cited by 2 | Viewed by 3786
Abstract
Shipping traffic is recognised as the main man-noise source of the anthropogenic noise generated in the marine environment. The underwater acoustic pollution is increased due to the increment of the human activity at seas supposing a threat for marine habitats. The ship as [...] Read more.
Shipping traffic is recognised as the main man-noise source of the anthropogenic noise generated in the marine environment. The underwater acoustic pollution is increased due to the increment of the human activity at seas supposing a threat for marine habitats. The ship as acoustic source must be understood and controlled to manage the maritime areas both in time and space to reduce the impact of noise in marine fauna. Shipping noise is mainly composed of flow noise, propeller noise and machinery noise. This research is focused on the analysis and estimation of the underwater radiated noise generated by the vibrations of the onboard machinery or structure-borne noise based on the calculation of the transfer function. This function relates the acceleration levels of the vibrations of the hull’s panels and the radiated noise by them using the radiation efficiency. Different analytical methods to estimate the radiation efficiency are presented and compared with data collected at sea. The measurements are performed acquiring simultaneously acceleration and acoustic levels by means on accelerometers installed on the hull’s panels at different positions and hydrophones deployed close to the bow, middle and stern of the ship. The analysis of the transmission of the vibrations along the ships is performed using the data from different locations of the hydrophones. The quality of the measurements is analysed using the coherence function through the spectral correlation between the measurement of vibrations and acoustic levels. On the other hand, signal-to-noise ratio is computed to verify the strength of the noise sources. The computed transfer function is used to predict the underwater radiated noise from vibrations showing differences less than 2 dB re to 1 μPa2. Full article
(This article belongs to the Section Environmental Sensing)
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14 pages, 4751 KiB  
Article
User-Driven Relay Beamforming for mmWave Massive Analog-Relay MIMO
by Masashi Iwabuchi, Yoghitha Ramamoorthi and Kei Sakaguchi
Sensors 2023, 23(2), 1034; https://doi.org/10.3390/s23021034 - 16 Jan 2023
Cited by 3 | Viewed by 1491
Abstract
Sixth-generation mobile communication (6G) aims to further improve capacity and reliability by controlling the radio propagation environment. Millimeter wave (mmWave) high-frequency band communication offers large bandwidth at the cost of high attenuation, even for smaller distances. Due to this, fewer multiple input multiple [...] Read more.
Sixth-generation mobile communication (6G) aims to further improve capacity and reliability by controlling the radio propagation environment. Millimeter wave (mmWave) high-frequency band communication offers large bandwidth at the cost of high attenuation, even for smaller distances. Due to this, fewer multiple input multiple outputs (MIMO) multiplexing is possible at the base station (BS). Distributed analog relay nodes with beamforming capability improve the received power and MIMO multiplexing of mmWave communication. Due to limited signal processing, the analog relay node cannot perform beam search and tracking using these mmWave reference signals. The beam search and tracking are possible at BS or user equipment at the cost of increased control overhead. To reduce this overhead and provide relay-based 6G communication, we propose user-driven relay beamforming methods which can obtain the benefits of a massive analog relay MIMO. Assuming vehicular-to-everything (V2X) as a 6G application, we considered a relay-beam control method that uses the user information (location, velocity, acceleration, and direction of the terminal) contained in intelligent transport systems (ITS) messages called Cooperative Awareness Message (CAM). Simulation results show that the proposed method significantly reduces the overhead and the obtains benefits of the massive analog-relay MIMO. Furthermore, the accuracy of CAM’s location information, the control period, and the effects of UE mobility are evaluated and presented. The results also show that the proposed method can work effectively in future V2X applications. Full article
(This article belongs to the Special Issue Next Generation Radio Communication Technologies)
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28 pages, 14000 KiB  
Article
A Contention-Free Cooperative MAC Protocol for Eliminating Heterogenous Collisions in Vehicular Ad Hoc Networks
by Nyi Nyi Linn, Kai Liu and Qiang Gao
Sensors 2023, 23(2), 1033; https://doi.org/10.3390/s23021033 - 16 Jan 2023
Cited by 2 | Viewed by 1756
Abstract
In vehicular ad hoc networks (VANETs), efficient data dissemination to a specified number of vehicles with minimum collisions and limited access delay is critical for accident prevention in road safety. However, packet collisions have a significant impact on access delay, and they may [...] Read more.
In vehicular ad hoc networks (VANETs), efficient data dissemination to a specified number of vehicles with minimum collisions and limited access delay is critical for accident prevention in road safety. However, packet collisions have a significant impact on access delay, and they may lead to unanticipated link failure when a range of diversified collisions are combined due to complex traffic conditions and rapid changes in network topology. In this paper, we propose a distributed contention-free cooperative medium access control (CFC-MAC) protocol to reduce heterogenous collisions and unintended access delay in stochastic traffic scenarios. Firstly, we develop a cooperative communication system model and cooperative forwarding mechanism to explore the optimum road path between the source and destination by identifying the potential cooperative vehicles. Secondly, we propose a vectorized trajectory estimation mechanism to suppress merging collisions by identifying the relative velocity of vehicles with different speeds in a specific time interval. Based on the case study, typical heterogeneous collisions and aggregated heterogeneous collisions at dissociated positions and associated positions are investigated. In both cases, we propose the corresponding collision-resolving mechanisms by methodically recapturing the colliding time slot or acquiring the available free time slots after identifying the access vehicles and comparing the received signal strengths. Performance analysis for collision probability and access delay is conducted. Finally, the simulation results show that the proposed protocol can achieve deterministic access delay and a minimal collision rate, substantially outperforming the existing solutions. Full article
(This article belongs to the Special Issue Sensor Networks for Vehicular Communications)
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9 pages, 1657 KiB  
Article
Effect of a Passive Exosuit on Sit-to-Stand Performance in Geriatric Patients Measured by Body-Worn Sensors—A Pilot Study
by Ulrich Lindemann, Jana Krespach, Urban Daub, Marc Schneider, Kim S. Sczuka and Jochen Klenk
Sensors 2023, 23(2), 1032; https://doi.org/10.3390/s23021032 - 16 Jan 2023
Viewed by 1569
Abstract
Standing up from a seated position is a prerequisite for any kind of physical mobility but many older persons have problems with the sit-to-stand (STS) transfer. There are several exosuits available for industrial work, which might be adapted to the needs of older [...] Read more.
Standing up from a seated position is a prerequisite for any kind of physical mobility but many older persons have problems with the sit-to-stand (STS) transfer. There are several exosuits available for industrial work, which might be adapted to the needs of older persons to support STS transfers. However, objective measures to quantify and evaluate such systems are needed. The aim of this study was to quantify the possible support of an exosuit during the STS transfer of geriatric patients. Twenty-one geriatric patients with a median age of 82 years (1.–3.Q. 79–84 years) stood up at a normal pace (1) from a chair without using armrests, (2) with using armrests and (3) from a bed with pushing off, each condition with and without wearing an exosuit. Peak angular velocity of the thighs was measured by body-worn sensors. It was higher when standing up with exosuit support from a bed (92.6 (1.–3.Q. 84.3–116.2)°/s versus 79.7 (1.–3.Q. 74.6–98.2)°/s; p = 0.014) and from a chair with armrests (92.9 (1.–3.Q. 78.3–113.0)°/s versus 77.8 (1.–3.Q. 59.3–100.7)°/s; p = 0.089) compared to no support. There was no effect of the exosuit when standing up from a chair without using armrests. In general, it was possible to quantify the support of the exosuit using sensor-measured peak angular velocity. These results suggest that depending on the STS condition, an exosuit can support older persons during the STS transfer. Full article
(This article belongs to the Special Issue Wearable Sensor Technologies for Physiological and Environmental Monitoring)
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11 pages, 3623 KiB  
Communication
Design of a CMOS Image Sensor with Bi-Directional Gamma-Corrected Digital-Correlated Double Sampling
by Jaehee Cho, Hyunseon Choo, Suhyeon Lee, Seungju Yoon, Gyuwon Kam and Sooyoun Kim
Sensors 2023, 23(2), 1031; https://doi.org/10.3390/s23021031 - 16 Jan 2023
Cited by 2 | Viewed by 1699
Abstract
We present a 640 × 480 CMOS image sensor (CIS) with in-circuit bi-directional gamma correction with a proposed digital-correlated double sampling (CDS) structure. To operate the gamma correction in the CIS, the transfer function of the analog-to-digital converter can be changed by controlling [...] Read more.
We present a 640 × 480 CMOS image sensor (CIS) with in-circuit bi-directional gamma correction with a proposed digital-correlated double sampling (CDS) structure. To operate the gamma correction in the CIS, the transfer function of the analog-to-digital converter can be changed by controlling the clock frequency of the counter using analog CDS. However, the analog CDS is vulnerable to capacitor mismatch, clock feedthrough, etc. Therefore, we propose a digital-CDS method with a hold-and-go counter structure to operate the bi-directional gamma correction in the CIS. The proposed CIS achieves a 10-bit resolution using a global log-exponential counter and configurable column reset counter with a resolution of 8/9 bits. The sensor was fabricated in a 0.11 μm CIS process, and the full chip area was 5.9 mm × 5.24 mm. The measurement results showed a maximum SNR improvement of 10.41% with the proposed bi-directional gamma-corrected digital-CDS with the hold-and-go counter. The total power consumption was 6.3 mW at a rate of 16.6 frames per second with analog, pixel, and digital supply voltages of 3.3 V, 3.3 V, and 1.5 V, respectively. Full article
(This article belongs to the Section Physical Sensors)
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13 pages, 4813 KiB  
Article
A Novel Adaptive Time-Frequency Filtering Approach to Enhance the Ultrasonic Inspection of Stainless Steel Structures
by Biao Wu, Haitao Yang, Yong Huang, Wensong Zhou and Xiaohui Liu
Sensors 2023, 23(2), 1030; https://doi.org/10.3390/s23021030 - 16 Jan 2023
Cited by 1 | Viewed by 1956
Abstract
Ultrasonic nondestructive testing (NDT) provides a valuable insight into the integrity of stainless steel structures, but the noise caused by the scattering of stainless steel microstructure often limits the effectiveness of inspection. This work presents a novel adaptive filtering approach to enhance the [...] Read more.
Ultrasonic nondestructive testing (NDT) provides a valuable insight into the integrity of stainless steel structures, but the noise caused by the scattering of stainless steel microstructure often limits the effectiveness of inspection. This work presents a novel adaptive filtering approach to enhance the signal-to-noise ratio (SNR) of a measured ultrasonic signal from the inspection of a stainless steel component, enabling the detection of hidden flaws under strong noise. After the spectral modeling of the noisy ultrasonic NDT signal, the difference between the spectral characteristics of a flaw echo and that of grain noise is highlighted, and a reference spectrum model to estimate the frequency spectrum of the echo reflected by any possible flaw is developed. Then, the signal is segmented and the similarity between the spectra of data segments and the reference spectra is evaluated quantitatively by the spectral similarity index (SSI). Based on this index, an adaptive time-frequency filtering scheme is proposed. Each data segment is processed by the filtering to suppress the energy of noise. The processed data segments are recombined to generate the de-noised signal after multiplying weighting coefficients, which again is determined by the SSI. The performance of the proposed method for SNR enhancement is evaluated by both the simulated and experimental signal and the effectiveness has been successfully demonstrated. Full article
(This article belongs to the Special Issue Smart Sensors for Structural Health Monitoring and Nondestructive Evaluation)
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13 pages, 2768 KiB  
Article
Lead-Free Piezoelectric Acceleration Sensor Built Using a (K,Na)NbO3 Bulk Ceramic Modified by Bi-Based Perovskites
by Min-Ku Lee, Byung-Hoon Kim and Gyoung-Ja Lee
Sensors 2023, 23(2), 1029; https://doi.org/10.3390/s23021029 - 16 Jan 2023
Cited by 2 | Viewed by 2343
Abstract
Piezoelectric accelerometers using a lead-free (K,Na)NbO3 (KNN) piezoceramic modified by a mixture of two Bi-based perovskites, Bi(Na,K,Li)ZrO3 (BNKLZ) and BiScO3 (BS), were designed, fabricated and characterized. Ring-shaped ceramics were prepared using a conventional solid-state reaction method for integration into a [...] Read more.
Piezoelectric accelerometers using a lead-free (K,Na)NbO3 (KNN) piezoceramic modified by a mixture of two Bi-based perovskites, Bi(Na,K,Li)ZrO3 (BNKLZ) and BiScO3 (BS), were designed, fabricated and characterized. Ring-shaped ceramics were prepared using a conventional solid-state reaction method for integration into a compression-mode accelerometer. A beneficial rhombohedral–tetragonal (R–T) phase boundary structure, especially enriched with T phase, was produced by modifying intrinsic phase transition temperatures, yielding a large piezoelectric charge coefficient d33 (310 pC/N) and a high Curie temperature Tc (331 °C). Using finite element analyses with metamodeling techniques, four optimum accelerometer designs were obtained with high magnitudes of charge sensitivity Sq and resonant frequency fr, as evidenced by two key performance indicators having a trade-off relation. Finally, accelerometer sensor prototypes based on the proposed designs were fabricated using the KNN-BNKLZ-BS ceramic rings, which exhibited high levels of Sq (55.1 to 223.8 pC/g) and mounted fr (14.1 to 28.4 kHz). Perfect charge-to-acceleration linearity as well as broad flat frequency ranges were achieved with excellent reliability. These outstanding sensing performances confirm the potential application of the modified-KNN ceramic in piezoelectric sensors. Full article
(This article belongs to the Section Electronic Sensors)
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16 pages, 6585 KiB  
Article
A Dilated Residual Network for Turbine Blade ICT Image Artifact Removal
by Rui Han, Fengying Zeng, Jing Li, Zhenwen Yao, Wenhua Guo and Jiyuan Zhao
Sensors 2023, 23(2), 1028; https://doi.org/10.3390/s23021028 - 16 Jan 2023
Cited by 1 | Viewed by 1244
Abstract
Artifacts are divergent strip artifacts or dark stripe artifacts in Industrial Computed Tomography (ICT) images due to large differences in density among the components of scanned objects, which can significantly distort the actual structure of scanned objects in ICT images. The presence of [...] Read more.
Artifacts are divergent strip artifacts or dark stripe artifacts in Industrial Computed Tomography (ICT) images due to large differences in density among the components of scanned objects, which can significantly distort the actual structure of scanned objects in ICT images. The presence of artifacts can seriously affect the practical application effectiveness of ICT in defect detection and dimensional measurement. In this paper, a series of convolution neural network models are designed and implemented based on preparing the ICT image artifact removal datasets. Our findings indicate that the RF (receptive field) and the spatial resolution of network can significantly impact the effectiveness of artifact removal. Therefore, we propose a dilated residual network for turbine blade ICT image artifact removal (DRAR), which enhances the RF of the network while maintaining spatial resolution with only a slight increase in computational load. Extensive experiments demonstrate that the DRAR achieves exceptional performance in artifact removal. Full article
(This article belongs to the Section Fault Diagnosis & Sensors)
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16 pages, 25853 KiB  
Article
Real Depth-Correction in Ground Penetrating RADAR Data Analysis for Bridge Deck Evaluation
by Sepehr Pashoutani and Jinying Zhu
Sensors 2023, 23(2), 1027; https://doi.org/10.3390/s23021027 - 16 Jan 2023
Cited by 3 | Viewed by 1811
Abstract
When ground penetrating radar (GPR) is used for the non-destructive evaluation of concrete bridge decks, the rebar reflection amplitudes should be corrected for rebar depths to account for the geometric spreading and material attenuation of the electromagnetic wave in concrete. Most current depth-correction [...] Read more.
When ground penetrating radar (GPR) is used for the non-destructive evaluation of concrete bridge decks, the rebar reflection amplitudes should be corrected for rebar depths to account for the geometric spreading and material attenuation of the electromagnetic wave in concrete. Most current depth-correction methods assume a constant EM wave velocity in the entire bridge deck and correct GPR amplitudes based on the two-way travel time (TWTT) instead of the actual rebar depth. In this paper, we proposed a depth-correction algorithm based on the real rebar depths. To compare different depth-correction methods, we used gprMax software to simulate GPR signals in four models with various dielectric constants and conductivity. The comparison shows that the TWTT-based depth-correction method tends to over-correct GPR amplitudes so that underestimates the deterioration level of concrete decks at certain locations. Two depth-based correction methods are proposed that use migrated amplitudes and further normalize the corrected amplitude by rebar depth (attenuation rate). These methods are then applied to GPR data collected on two bridges, and the results were validated by other NDE methods and chloride concentration test. Full article
(This article belongs to the Special Issue Intelligent Structural Health Monitoring for Modern Industrial and Civil Assets)
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19 pages, 3376 KiB  
Article
Automatic Detection of Cognitive Impairment with Virtual Reality
by Farzana A. Mannan, Lilla A. Porffy, Dan W. Joyce, Sukhwinder S. Shergill and Oya Celiktutan
Sensors 2023, 23(2), 1026; https://doi.org/10.3390/s23021026 - 16 Jan 2023
Cited by 2 | Viewed by 2257
Abstract
Cognitive impairment features in neuropsychiatric conditions and when undiagnosed can have a severe impact on the affected individual’s safety and ability to perform daily tasks. Virtual Reality (VR) systems are increasingly being explored for the recognition, diagnosis and treatment of cognitive impairment. In [...] Read more.
Cognitive impairment features in neuropsychiatric conditions and when undiagnosed can have a severe impact on the affected individual’s safety and ability to perform daily tasks. Virtual Reality (VR) systems are increasingly being explored for the recognition, diagnosis and treatment of cognitive impairment. In this paper, we describe novel VR-derived measures of cognitive performance and show their correspondence with clinically-validated cognitive performance measures. We use an immersive VR environment called VStore where participants complete a simulated supermarket shopping task. People with psychosis (k=26) and non-patient controls (k=128) participated in the study, spanning ages 20–79 years. The individuals were split into two cohorts, a homogeneous non-patient cohort (k=99 non-patient participants) and a heterogeneous cohort (k=26 patients, k=29 non-patient participants). Participants’ spatio-temporal behaviour in VStore is used to extract four features, namely, route optimality score, proportional distance score, execution error score, and hesitation score using the Traveling Salesman Problem and explore-exploit decision mathematics. These extracted features are mapped to seven validated cognitive performance scores, via linear regression models. The most statistically important feature is found to be the hesitation score. When combined with the remaining extracted features, the multiple linear regression model resulted in statistically significant results with R2 = 0.369, F-Stat = 7.158, p(F-Stat) = 0.000128. Full article
(This article belongs to the Special Issue Intelligent Systems and Sensors for Assistive Technology)
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20 pages, 4958 KiB  
Article
DCP-SLAM: Distributed Collaborative Partial Swarm SLAM for Efficient Navigation of Autonomous Robots
by Huma Mahboob, Jawad N. Yasin, Suvi Jokinen, Mohammad-Hashem Haghbayan, Juha Plosila and Muhammad Mehboob Yasin
Sensors 2023, 23(2), 1025; https://doi.org/10.3390/s23021025 - 16 Jan 2023
Cited by 4 | Viewed by 2588
Abstract
Collaborative robots represent an evolution in the field of swarm robotics that is pervasive in modern industrial undertakings from manufacturing to exploration. Though there has been much work on path planning for autonomous robots employing floor plans, energy-efficient navigation of autonomous robots in [...] Read more.
Collaborative robots represent an evolution in the field of swarm robotics that is pervasive in modern industrial undertakings from manufacturing to exploration. Though there has been much work on path planning for autonomous robots employing floor plans, energy-efficient navigation of autonomous robots in unknown environments is gaining traction. This work presents a novel methodology of low-overhead collaborative sensing, run-time mapping and localization, and navigation for robot swarms. The aim is to optimize energy consumption for the swarm as a whole rather than individual robots. An energy- and information-aware management algorithm is proposed to optimize the time and energy required for a swarm of autonomous robots to move from a launch area to the predefined destination. This is achieved by modifying the classical Partial Swarm SLAM technique, whereby sections of objects discovered by different members of the swarm are stitched together and broadcast to members of the swarm. Thus, a follower can find the shortest path to the destination while avoiding even far away obstacles in an efficient manner. The proposed algorithm reduces the energy consumption of the swarm as a whole due to the fact that the leading robots sense and discover respective optimal paths and share their discoveries with the followers. The simulation results show that the robots effectively re-optimized the previous solution while sharing necessary information within the swarm. Furthermore, the efficiency of the proposed scheme is shown via comparative results, i.e., reducing traveling distance by 13% for individual robots and up to 11% for the swarm as a whole in the performed experiments. Full article
(This article belongs to the Special Issue Advanced Sensing and Control Technologies for Autonomous Robots)
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15 pages, 2999 KiB  
Article
Low Cost Magnetic Field Control for Disabled People
by Daniel Acosta, Bibiana Fariña, Jonay Toledo and Leopoldo Acosta Sanchez
Sensors 2023, 23(2), 1024; https://doi.org/10.3390/s23021024 - 16 Jan 2023
Cited by 2 | Viewed by 1462
Abstract
Our research presents a cost-effective navigation system for electric wheelchairs that utilizes the tongue as a human–machine interface (HMI) for disabled individuals. The user controls the movement of the wheelchair by wearing a small neodymium magnet on their tongue, which is held in [...] Read more.
Our research presents a cost-effective navigation system for electric wheelchairs that utilizes the tongue as a human–machine interface (HMI) for disabled individuals. The user controls the movement of the wheelchair by wearing a small neodymium magnet on their tongue, which is held in place by a suction pad. The system uses low-cost electronics and sensors, including two electronic compasses, to detect the position of the magnet in the mouth. One compass estimates the magnet’s position while the other is used as a reference to compensate for static magnetic fields. A microcontroller processes the data using a computational algorithm that takes the mathematical formulations of the magnetic fields as input in real time. The system has been tested using real data to control an electric wheelchair, and it has been shown that a trained user can effectively use tongue movements as an interface for the wheelchair or a computer. Full article
(This article belongs to the Special Issue Assistance Robotics and Sensors)
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18 pages, 995 KiB  
Article
Dual Residual Denoising Autoencoder with Channel Attention Mechanism for Modulation of Signals
by Ruifeng Duan, Ziyu Chen, Haiyan Zhang, Xu Wang, Wei Meng and Guodong Sun
Sensors 2023, 23(2), 1023; https://doi.org/10.3390/s23021023 - 16 Jan 2023
Cited by 5 | Viewed by 1864
Abstract
Aiming to address the problems of the high bit error rate (BER) of demodulation or low classification accuracy of modulation signals with a low signal-to-noise ratio (SNR), we propose a double-residual denoising autoencoder method with a channel attention mechanism, referred to as DRdA-CA, [...] Read more.
Aiming to address the problems of the high bit error rate (BER) of demodulation or low classification accuracy of modulation signals with a low signal-to-noise ratio (SNR), we propose a double-residual denoising autoencoder method with a channel attention mechanism, referred to as DRdA-CA, to improve the SNR of modulation signals. The proposed DRdA-CA consists of an encoding module and a decoding module. A squeeze-and-excitation (SE) ResNet module containing one residual connection is modified and then introduced into the autoencoder as the channel attention mechanism, to better extract the characteristics of the modulation signals and reduce the computational complexity of the model. Moreover, the other residual connection is further added inside the encoding and decoding modules to optimize the network degradation problem, which is beneficial for fully exploiting the multi-level features of modulation signals and improving the reconstruction quality of the signal. The ablation experiments prove that both the improved SE module and dual residual connections in the proposed method play an important role in improving the denoising performance. The subsequent experimental results show that the proposed DRdA-CA significantly improves the SNR values of eight modulation types in the range of −12 dB to 8 dB. Especially for 16QAM and 64QAM, the SNR is improved by 8.38 dB and 8.27 dB on average, respectively. Compared to the DnCNN denoising method, the proposed DRdA-CA makes the average classification accuracy increase by 67.59∼74.94% over the entire SNR range. When it comes to the demodulation, compared with the RLS and the DnCNN denoising algorithms, the proposed denoising method reduces the BER of 16QAM by an average of 63.5% and 40.5%, and reduces the BER of 64QAM by an average of 46.7% and 18.6%. The above results show that the proposed DRdA-CA achieves the optimal noise reduction effect. Full article
(This article belongs to the Special Issue Advances in Cognitive Radio Networking and Communications)
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15 pages, 6755 KiB  
Article
A Novel Piecewise Tri-Stable Stochastic Resonance System Driven by Dichotomous Noise
by Shuai Zhao and Peiming Shi
Sensors 2023, 23(2), 1022; https://doi.org/10.3390/s23021022 - 16 Jan 2023
Cited by 3 | Viewed by 1214
Abstract
Stochastic resonance (SR) has been widely studied as a means of signal processing since its conception. Since SR is different from other denoising methods in nature, it can be used for not only feature extraction but also signal enhancement. Additive white Gaussian noise [...] Read more.
Stochastic resonance (SR) has been widely studied as a means of signal processing since its conception. Since SR is different from other denoising methods in nature, it can be used for not only feature extraction but also signal enhancement. Additive white Gaussian noise (AWGN) is often used as a driving source in SR research due to its convenience in numerical simulation and uniform distribution, but as a special noise, it is of great significance to study the SR principle of dichotomous noise as a driving source for nonlinear dynamics. In this paper, the method of piecewise tri-stable SR (PTSR) driven by dichotomous noise is studied, and it is verified that signal enhancement can still be achieved in the PTSR system. At the same time, the influence of the parameters of the PTSR system, periodic signal, and dichotomous noise on the mean of signal-to-noise ratio gain (SNR-GM) is analyzed. Finally, dichotomous noise and AWGN are used as the driving sources of the PTSR system, and the signal enhancement ability and noise resistance ability of the two drivers are compared. Full article
(This article belongs to the Section Fault Diagnosis & Sensors)
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21 pages, 4523 KiB  
Article
Bearing Fault Diagnosis Using a Hybrid Fuzzy V-Structure Fault Estimator Scheme
by Farzin Piltan and Jong-Myon Kim
Sensors 2023, 23(2), 1021; https://doi.org/10.3390/s23021021 - 16 Jan 2023
Cited by 6 | Viewed by 1366
Abstract
Bearings are critical components of motors. However, they can cause several issues. Proper and timely detection of faults in the bearings can play a decisive role in reducing damage to the entire system, thereby reducing economic losses. In this study, a hybrid fuzzy [...] Read more.
Bearings are critical components of motors. However, they can cause several issues. Proper and timely detection of faults in the bearings can play a decisive role in reducing damage to the entire system, thereby reducing economic losses. In this study, a hybrid fuzzy V-structure fuzzy fault estimator was used for fault diagnosis and crack size identification in the bearing using vibration signals. The estimator was designed based on the combination of a fuzzy algorithm and a V-structure approach to reduce the oscillation and improve the unknown condition’s estimation and prediction in using the V-structure method. The V-structure surface is developed by the proposed fuzzy algorithm, which reduces the vibrations and improves the stability. In addition, the parallel fuzzy method is used to improve the robustness and stability of the V-structure algorithm. For data modeling, the proposed combination of an external autoregression error, a Laguerre filter, and a support vector regression algorithm was employed. Finally, the support vector machine algorithm was used for data classification and crack size detection. The effectiveness of the proposed approach was evaluated by leveraging the vibration signals provided in the Case Western Reserve University bearing dataset. The dataset consists of four conditions: normal, ball failure, inner fault, and outer fault. The results showed that the average accuracy of fault classification and crack size identification using the hybrid fuzzy V-structure fuzzy fault estimation algorithm was 98.75% and 98%, respectively. Full article
(This article belongs to the Special Issue Feature Papers in Fault Diagnosis & Sensors Section 2022)
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18 pages, 3711 KiB  
Article
Application of Neural Network in Predicting H2S from an Acid Gas Removal Unit (AGRU) with Different Compositions of Solvents
by Mohd Hakimi, Madiah Binti Omar and Rosdiazli Ibrahim
Sensors 2023, 23(2), 1020; https://doi.org/10.3390/s23021020 - 16 Jan 2023
Cited by 5 | Viewed by 2097
Abstract
The gas sweetening process removes hydrogen sulfide (H2S) in an acid gas removal unit (AGRU) to meet the gas sales’ specification, known as sweet gas. Monitoring the concentration of H2S in sweet gas is crucial to avoid operational and [...] Read more.
The gas sweetening process removes hydrogen sulfide (H2S) in an acid gas removal unit (AGRU) to meet the gas sales’ specification, known as sweet gas. Monitoring the concentration of H2S in sweet gas is crucial to avoid operational and environmental issues. This study shows the capability of artificial neural networks (ANN) to predict the concentration of H2S in sweet gas. The concentration of N-methyldiethanolamine (MDEA) and Piperazine (PZ), temperature and pressure as inputs, and the concentration of H2S in sweet gas as outputs have been used to create the ANN network. Two distinct backpropagation techniques with various transfer functions and numbers of neurons were used to train the ANN models. Multiple linear regression (MLR) was used to compare the outcomes of the ANN models. The models’ performance was assessed using the mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The findings demonstrate that ANN trained by the Levenberg–Marquardt technique, equipped with a logistic sigmoid (logsig) transfer function with three neurons achieved the highest R2 (0.966) and the lowest MAE (0.066) and RMSE (0.122) values. The findings suggested that ANN can be a reliable and accurate prediction method in predicting the concentration of H2S in sweet gas. Full article
(This article belongs to the Special Issue Intelligent Sensors and Machine Learning)
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17 pages, 2523 KiB  
Article
Inferential Composition Control of a Distillation Column Using Active Disturbance Rejection Control with Soft Sensors
by Fahad Al Kalbani and Jie Zhang
Sensors 2023, 23(2), 1019; https://doi.org/10.3390/s23021019 - 16 Jan 2023
Viewed by 1985
Abstract
This paper presents the integration of active disturbance rejection control (ADRC) with soft sensors for enhancing the composition control performance in a distillation column. Static and dynamic soft sensors are developed to estimate the top and bottom product compositions using multiple tray temperatures. [...] Read more.
This paper presents the integration of active disturbance rejection control (ADRC) with soft sensors for enhancing the composition control performance in a distillation column. Static and dynamic soft sensors are developed to estimate the top and bottom product compositions using multiple tray temperatures. In order to cope with the collinearity issues in tray temperature measurements, static and dynamic principal component regression is used in developing the soft sensors. The soft sensor outputs are introduced as the feedback signals to ADRC. This control scheme is termed as “inferential ADRC control”. Static control offsets are eliminated through mean updating in the soft-sensor models. The effectiveness of the proposed control scheme is demonstrated on a benchmark simulated methanol-water distillation column. Full article
(This article belongs to the Special Issue Intelligent Sensing and Automatic Device for Industrial Process)
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