Paper
10 October 2023 Missing identification of glass insulators based on YOLO v5 algorithm
Min Xie, Xiaogang Li, Chenlong Zhao, Cheng Xu, Zhuhong Liu
Author Affiliations +
Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127990Z (2023) https://doi.org/10.1117/12.3006297
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia
Abstract
As one of the three main insulators, glass insulators are widely used in transmission lines. Due to its own characteristics, glass insulators are prone to self explosion during use, which then cause insulator missing and easily lead to power accidents. With the progress of unmanned aerial vehicle inspection and other inspection technologies, reliable identification of missing insulators based on image recognition become very important. This article uses the most advanced YOLO v5 object detection algorithm to identify the missing of glass insulators. The detection rate for insulators is about 97.2%, and the detection rate for missing glass insulators is about 98.6%, with an average mAP@0.5 of 97.9%.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Min Xie, Xiaogang Li, Chenlong Zhao, Cheng Xu, and Zhuhong Liu "Missing identification of glass insulators based on YOLO v5 algorithm", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127990Z (10 October 2023); https://doi.org/10.1117/12.3006297
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KEYWORDS
Dielectrics

Detection and tracking algorithms

Object detection

Inspection

Target recognition

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