Visual monitoring system for operation and maintenance of converter station based on sensor fusion
Authors: 
Tao Huang, Ke Wu, Zhiwu Xiong, Wei Pan, Guobing LiuAuthors Info & Claims
Tao Huang, Ke Wu, Zhiwu Xiong, Wei Pan, Guobing LiuAuthors Info & ClaimsPages 874 - 881
Abstract
To monitor the operation status of converter station equipment during operation and maintenance operations in real time, a visual monitoring system for converter station operation and maintenance based on sensor fusion is designed. Design a three-dimensional virtual visualization scene model based on AR intelligent devices, and obtain converter station environment and equipment data through a multi-sensor fusion module; Transform and decompose sensor signals using discrete wavelet transform and wavelet packet energy spectrum; Innovatively adopt operation and maintenance monitoring algorithms to analyze and model the associated data, predict the operation status of converter station equipment through RBF neural network algorithms, and map the operation status of converter station equipment nonlinearly based on feature vectors; Real-time monitoring of operation site images to achieve visual monitoring of operation and maintenance operations at the converter station. The experimental results show that the designed system can monitor the operation status of converter station equipment during operation and maintenance operations in real time, and distinguish equipment failures. The monitoring results of 8 patrol inspection items are consistent with the actual results, which can assist the operation and maintenance personnel in the smooth development of maintenance work.
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- Visual monitoring system for operation and maintenance of converter station based on sensor fusion
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Published In
January 2024
969 pages
ISBN:9798400716638
DOI:10.1145/3674225
Copyright © 2024 ACM.
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Association for Computing Machinery
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Publication History
Published: 31 July 2024
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PEAI 2024
PEAI 2024: 2024 International Conference on Power Electronics and Artificial Intelligence
January 19 - 21, 2024
Xiamen, China
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