Review
Engineering, Electrical & Electronic
Runjie He, Chuanxin Teng, Santosh Kumar, Carlos Marques, Rui Min
Summary: Polymer optical fiber (POF) level sensors have the potential to be widely used in liquid level sensing due to their safety, corrosion resistance, anti-electromagnetic interference, electrical isolation, compactness, efficiency, and flexibility. This review provides an overview of POF liquid level sensing, including materials, operation principles, and applications.
IEEE SENSORS JOURNAL
(2022)
Article
Chemistry, Analytical
Fanli Meng, Xue Shi, Zhenyu Yuan, Hanyang Ji, Wenbo Qin, YanBai Shen, Chaoyang Xing
Summary: This paper successfully detected four alcohol homologue gases using a ZnO gas sensor with dynamic temperature modulation method, achieving a recognition accuracy of 97.62% after optimization with decision tree classification algorithm.
SENSORS AND ACTUATORS B-CHEMICAL
(2022)
Article
Engineering, Electrical & Electronic
Huanlai Xing, Zhiwen Xiao, Rong Qu, Zonghai Zhu, Bowen Zhao
Summary: This article proposes an efficient federated distillation learning system (EFDLS) for multitask time series classification (TSC). It introduces two novel components: a feature-based student-teacher (FBST) framework and a distance-based weights matching (DBWM) scheme. Experimental results demonstrate that EFDLS outperforms other federated learning algorithms in multiple datasets and achieves higher mean accuracy compared to a single-task baseline.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Multidisciplinary
Yuqing Zhou, Gaofeng Zhi, Wei Chen, Qijia Qian, Dedao He, Bintao Sun, Weifang Sun
Summary: This research proposed a new improved multi-scale edge-labeling graph neural network (MEGNN) to enhance the recognition accuracy of DL-based TCM under small samples. By expanding each channel signal of a cutting force sensor to multi-dimensional data, the MEGNN method outperforms three DL-based methods (CNN, AlexNet, ResNet) in experiments.
Article
Chemistry, Analytical
Qingting Li, Wen Zeng, Yanqiong Li
Summary: This article reviews the NO2 gas sensor based on metal oxides. It discusses the hazards of NO2, the disadvantages of chemiresistive sensors based on metal oxides, and different sensitive materials. It also explores NO2 gas sensors based on metal oxides from various aspects such as morphology, preparation, modification, doping, and composite.
SENSORS AND ACTUATORS B-CHEMICAL
(2022)
Article
Chemistry, Analytical
Chia-Nan Wang, Fu-Chiang Yang, Van Thanh Tien Nguyen, Nhut T. M. Vo
Summary: This study proposed a novel approach to improve centrifugal pump performance by establishing a numerical model and applying artificial intelligence algorithm to optimize the pump design, resulting in improved performances.
Article
Automation & Control Systems
Jing Li, Hui Qin, Junzheng Wang, Jiehao Li
Summary: In this article, a method for robot navigation based on OpenStreetMap (OSM) is proposed, which combines road network information and local perception information. The use of OSM provides accurate global path planning, while multisensor fusion offers local information for obstacle detection and local path planning. Experimental results show that the method has high accuracy and robustness in real complex environments.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Automation & Control Systems
Li Sun, Wenchao Xue, Donghai Li, Hongxia Zhu, Zhi-gang Su
Summary: This article proposes a quantitative tuning rule for the time-delayed ADRC (TD-ADRC) structure in power plant processes and validates its effectiveness through simulation and experiments.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Chemistry, Analytical
Abdulaziz Fatani, Abdelghani Dahou, Mohammed A. A. Al-qaness, Songfeng Lu, Mohamed Abd Elaziz
Summary: In this study, a new intrusion detection system was developed utilizing swarm intelligence algorithms for feature extraction and selection. The system employed neural networks and the Aquila optimizer for this purpose. Performance evaluation on four public datasets demonstrated the competitive nature of the developed approach.
Review
Chemistry, Analytical
Sagnik Das, Subhajit Mojumder, Debdulal Saha, Mrinal Pal
Summary: In this review, the significant effects of various parameters on the sensing behavior of semiconductor metal oxide (SMO) based chemiresistive gas sensors have been discussed in detail. The study systematically reviewed the impact of different material and operating condition aspects on the gas sensing performance of SMO sensors. The importance of long-term stability and high-throughput synthesis techniques in practical applications was emphasized, and the future prospects of SMO-based sensors in personalized healthcare were briefly outlined.
SENSORS AND ACTUATORS B-CHEMICAL
(2022)
Article
Automation & Control Systems
Yang Li, Zhongbao Wei, Binyu Xiong, D. Mahinda Vilathgamuwa
Summary: This article proposes a computationally efficient state estimation method for lithium-ion batteries based on a degradation-conscious high-fidelity electrochemical-thermal model. The algorithm uses an ensemble-based state estimator with the singular evolutive interpolated Kalman filter (SEIKF) to ease the computational burden caused by the nonlinear nature of the battery model. Unlike existing schemes, the proposed algorithm ensures mass conservation without additional constraints, simplifying the tuning process and improving convergence speed. The proposed scheme addresses model uncertainty and measurement errors through adaptive adjustment of the SEIKF's error covariance matrices. Comparisons with well-established nonlinear estimation techniques show that the adaptive ensemble-based Li-ion battery state estimator provides excellent performance in terms of accuracy, computational speed, and robustness.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Automation & Control Systems
Yizhao Gao, Kailong Liu, Chong Zhu, Xi Zhang, Dong Zhang
Summary: This article presents a scheme using a simplified reduced-order electrochemical model and dual nonlinear filters for the reliable co-estimations of cell state-of-charge (SOC) and state-of-health (SOH). By accessing unmeasurable physical variables such as surface and bulk solid-phase concentration, the feasibility and performance of SOC estimator are revealed. Aging factors including loss of lithium ions, loss of active materials, and resistance increment are identified to improve the precision of SOC estimation for aged cells.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Chemistry, Analytical
Aitizaz Ali, Mohammed Amin Almaiah, Fahima Hajjej, Muhammad Fermi Pasha, Ong Huey Fang, Rahim Khan, Jason Teo, Muhammad Zakarya
Summary: This paper proposes a novel algorithm based on group theory and deep neural networks to address security issues in the IoT. By utilizing blockchain and homomorphic encryption techniques, a secure patient healthcare data access scheme is devised, providing better efficiency and security in current schemes for sharing digital healthcare data.
Article
Automation & Control Systems
Yi Xie, Wei Li, Xiaosong Hu, Manh-Kien Tran, Satyam Panchal, Michael Fowler, Yangjun Zhang, Kailong Liu
Summary: This article proposes a distributed spatial-temporal online correction algorithm for the coestimation of the state of charge (SOC) and state of temperature (SOT) of batteries, which is crucial for a battery management system in achieving a green industrial economy. The algorithm identifies the internal resistance and estimates SOC using an adaptive Kalman filter. It then couples SOC estimation with an online restoration algorithm for distributed temperature, using an improved fractal growth process. The proposed coestimation algorithm improves SOC estimation fidelity by up to 1.5% and maintains the mean relative error of SOT estimation within 8%.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Jiaxin Xiong, Jian Pan, Guangyi Chen, Xiao Zhang, Feng Ding
Summary: In this article, a sliding mode dual-channel disturbance rejection control method is proposed for the attitude control of a quadrotor under unknown disturbances. The proposed method compensates for the low-frequency and high-frequency components of the disturbances and reduces the influence of the virtual disturbance estimation error. The stability of the system is proved using Lyapunov theory.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Automation & Control Systems
Chaoying Yang, Kaibo Zhou, Jie Liu
Summary: This article proposes a graph-based feature extraction method for rotating machinery fault diagnosis. By converting raw data into graphs, hidden structural and topological information can be obtained. Experimental results verify the effectiveness of this method in fault diagnosis.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Review
Chemistry, Analytical
Debdyuti Mandal, Sourav Banerjee
Summary: This article introduces surface acoustic waves (SAWs) and their applications in sensors. By explaining the physics of guided SAWs and the piezoelectric materials used, it discusses how the materials and cuts can alter sensor functionality. It summarizes key electrode configurations and guidelines for generating different guided wave patterns, and explores the applications of SAW sensors in various fields and potential improvement plans in science and technology.
Article
Automation & Control Systems
Yonghao Miao, Boyao Zhang, Chenhui Li, Jing Lin, Dayi Zhang
Summary: This article introduces a new feature extraction method called Feature Mode Decomposition (FMD) for machinery fault. FMD decomposes different fault modes using adaptive FIR filters and takes into account the impulsiveness and periodicity of fault signals with the help of correlated Kurtosis. The superiority of FMD is demonstrated in adaptively and accurately decomposing fault modes and being robust to interferences and noise, using simulated and experimental data from bearing faults. Furthermore, FMD has been shown to outperform the popular Variational Mode Decomposition in machinery fault feature extraction.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Multidisciplinary
Asma Alsadat Mousavi, Chunwei Zhang, Sami F. Masri, Gholamreza Gholipour
Summary: Signal processing is crucial in vibration-based approaches and damage detection for structural health monitoring. The complete ensemble empirical mode decomposition with adaptive noise technique shows superior robustness and sensitivity in addressing damage location, classification, and detection compared to other decomposition techniques.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2022)
Article
Automation & Control Systems
Minh-Quang Tran, Meng-Kun Liu, Mahmoud Elsisi
Summary: This paper introduces a newly developed multi-sensor data fusion method for milling chatter detection. The proposed method has a low cost and easy implementation compared to traditional schemes. It utilizes microphone and accelerometer sensors to measure chatter during the milling process, and improves detection accuracy through optimizing parameter selection and feature elimination methods.
