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Diagnosis of Reverse-Connection Defects in High-Voltage Cable Cross-Bonded Grounding System Based on ARO-SVM.
Sensors (Basel)
January 2025
Hubei Key Laboratory of Power Equipment & System Security for Integrated Energy, School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China.
High-voltage (HV) cables are increasingly used in urban power grids, and their safe operation is critical to grid stability. Previous studies have analyzed various defects, including the open circuit in the sheath loop, the flooding in the cross-bonded link box, and the sheath grounding fault. However, there is a paucity of research on the defect of the reverse direction between the inner core and the outer shield of the coaxial cable.
View Article and Find Full Text PDFVirtual Node-Driven Cloud-Edge Collaborative Resource Scheduling for Surveillance with Visual Sensors.
Sensors (Basel)
January 2025
Intelligent Control Laboratory, Xi'an Research Institute of High Technology, Xi'an 710025, China.
For public security purposes, distributed surveillance systems are widely deployed in key areas. These systems comprise visual sensors, edge computing boxes, and cloud servers. Resource scheduling algorithms are critical to ensure such systems' robustness and efficiency.
View Article and Find Full Text PDFRWA-BFT: Reputation-Weighted Asynchronous BFT for Large-Scale IoT.
Sensors (Basel)
January 2025
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.
This paper introduces RWA-BFT, a reputation-weighted asynchronous Byzantine Fault Tolerance (BFT) consensus algorithm designed to address the scalability and performance challenges of blockchain systems in large-scale IoT scenarios. Traditional centralized IoT architectures often face issues such as single points of failure and insufficient reliability, while blockchain, with its decentralized and tamper-resistant properties, offers a promising solution. However, existing blockchain consensus mechanisms struggle to meet the high throughput, low latency, and scalability demands of IoT applications.
View Article and Find Full Text PDFRolling Bearing Fault Diagnosis Based on a Synchrosqueezing Wavelet Transform and a Transfer Residual Convolutional Neural Network.
Sensors (Basel)
January 2025
School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China.
This study proposes a novel rolling bearing fault diagnosis technique based on a synchrosqueezing wavelet transform (SWT) and a transfer residual convolutional neural network (TRCNN) designed to address the difficulties of feature extraction caused by the non-stationarity of fault signals, as well as the issue of low fault diagnosis accuracy resulting from small sample quantities. This approach transforms the one-dimensional vibration signal into time-frequency diagrams using an SWT based on complex Morlet wavelet basis functions, which redistributes (squeezes) the values of the wavelet coefficients at different localized points in a time-frequency plane to the estimated instantaneous frequencies. This allows the energy to be more fully concentrated in actual corresponding frequency components.
View Article and Find Full Text PDFOn the Performance of Energy Harvesting Dual-Hop Free-Space Optical Communication Systems with Secrecy Analysis.
Sensors (Basel)
January 2025
Informatics Institute, Istanbul Technical University, 34467 Istanbul, Turkey.
In this study, we present a dual-hop decode-and-forward relaying-based free-space optical (FSO) communication system. We consider utilizing simultaneous lightwave information and power transfer (SLIPT) with a time-splitting technique at the relay, where the direct current component of the received optical signal is harvested as a transmit power for the relay. It is assumed that the FSO links experience a Malaga turbulence channel with pointing errors.
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