Paper
6 February 2024 The AGV-based substation operation status inspection and monitoring method
Junqin Yao, Libin Qin, Xuefeng Ning
Author Affiliations +
Proceedings Volume 12979, Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023); 129795X (2024) https://doi.org/10.1117/12.3015322
Event: 9th International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023), 2023, Guilin, China
Abstract
The current conventional substation operation status inspection monitoring method mainly constructs the operation status judgment index based on the fusion monitoring information to realize the monitoring of equipment. However, this method may lead to poor monitoring effects due to the lack of effective processing of image data. In this regard, the AGV-based substation operation status inspection and monitoring method is proposed to address this problem. By optimizing the mechanical structure and driving method of the AGV intelligent inspection and handling vehicle, and processing the monitoring image data, we can construct the excitation function by combining a deep neural network to realize the judgment of substation operation status. In the experiment, the proposed method is verified for the monitoring effect. The analysis of the experimental results shows that the proposed method has a lower algorithm recall rate and has a more excellent monitoring effect when the proposed method is used to monitor the substation.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Junqin Yao, Libin Qin, and Xuefeng Ning "The AGV-based substation operation status inspection and monitoring method", Proc. SPIE 12979, Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023), 129795X (6 February 2024); https://doi.org/10.1117/12.3015322
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KEYWORDS
Inspection

Inspection equipment

Image processing

Design and modelling

Neural networks

Intelligence systems

Image analysis

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