Design of multi-antenna RFID passive bolt loosening fault location system based on the Internet of Things

Abstract Bolt connections are the most common form of connection in hydroelectric generator units. The manhole of spiral case in hydroelectric generator unit is highly susceptible to loosening and fatigue of the bolts due to long-term exposure to hydraulic vibrations, which can lead to bolt breakage and pose significant safety risks. To address the issue of bolt loosening fault localization in the manhole of spiral case in hydroelectric generator unit, a passive bolt loosening fault localization system based on the Internet of Things (IoT) and multi-antenna radio frequency identification (RFID) is designed. First, a tag identification model for multi-antenna RFID is developed, and an optimization control scheme for the multi-antenna system is proposed. Second, an improved virtual reference elimination (VIRE) algorithm for bolt loosening fault localization is proposed, integrating cubic spline interpolation and dynamic threshold (Th). The positioning accuracy of the algorithm is verified by modifying simulation parameters. Finally, a passive bolt loosening fault localization hardware system using multi-antenna RFID is constructed, and upper and lower machine testing programs are developed to achieve precise fault localization of the bolt loosening using the multi-antenna system. Experimental results demonstrate that the IoT-based multi-antenna RFID passive bolt loosening fault localization system can achieve rapid and stable detection of bolt loosening faults. The positioning accuracy of the proposed improved VIRE algorithm is enhanced by 99.15% and 30.95% compared to the LANDMARC and VIRE algorithms, respectively. This system offers a novel approach for the localization of bolt loosening faults in the manhole of spiral case of hydroelectric generator unit under complex operating conditions.

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Publication Details

Journal
Measurement Science and Technology
Published
2025-05-01
DOI
https://doi.org/10.1088/1361-6501/add28b
Citations
1
Primary Topic
Wireless Sensor Networks and IoT
Type
article
Field-Weighted Citation Impact
1.21

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article

Design of multi-antenna RFID passive bolt loosening fault location system based on the Internet of Things

Huijun Liang, Yan Ran, Luoping Lu, Jianwei Zhong et al.
1 citations
Measurement Science and Technology
Wireless Sensor Networks and IoT
1.21
article

Design of multi-antenna RFID passive bolt loosening fault location system based on the Internet of Things

Huijun Liang, Yan Ran, Luoping Lu, Jianwei Zhong, Xiangpeng Tian, Honghua Liao
article en
1 citations

Abstract

Abstract Bolt connections are the most common form of connection in hydroelectric generator units. The manhole of spiral case in hydroelectric generator unit is highly susceptible to loosening and fatigue of the bolts due to long-term exposure to hydraulic vibrations, which can lead to bolt breakage and pose significant safety risks. To address the issue of bolt loosening fault localization in the manhole of spiral case in hydroelectric generator unit, a passive bolt loosening fault localization system based on the Internet of Things (IoT) and multi-antenna radio frequency identification (RFID) is designed. First, a tag identification model for multi-antenna RFID is developed, and an optimization control scheme for the multi-antenna system is proposed. Second, an improved virtual reference elimination (VIRE) algorithm for bolt loosening fault localization is proposed, integrating cubic spline interpolation and dynamic threshold (Th). The positioning accuracy of the algorithm is verified by modifying simulation parameters. Finally, a passive bolt loosening fault localization hardware system using multi-antenna RFID is constructed, and upper and lower machine testing programs are developed to achieve precise fault localization of the bolt loosening using the multi-antenna system. Experimental results demonstrate that the IoT-based multi-antenna RFID passive bolt loosening fault localization system can achieve rapid and stable detection of bolt loosening faults. The positioning accuracy of the proposed improved VIRE algorithm is enhanced by 99.15% and 30.95% compared to the LANDMARC and VIRE algorithms, respectively. This system offers a novel approach for the localization of bolt loosening faults in the manhole of spiral case of hydroelectric generator unit under complex operating conditions.

Measurement Science and TechnologyVol. 36(5)
Minzu University of China (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 22%
Wireless Sensor Networks and IoT
1.21
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