Paper
13 May 2024 Research on identification and detection of foreign body intrusion for overhead lines
Yong Yu, Yanchao Sun, Yanlai Tang, Bowen Yin, Qi Wu, Chong Qu
Author Affiliations +
Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 1315964 (2024) https://doi.org/10.1117/12.3024317
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China
Abstract
In this paper, a method of automatic identification and detection of foreign body intrusion for overhead transmission lines is proposed, which can solve the problem of heavy workload in daily inspection for overhead transmission lines. The actual overhead line images captured by inspection drones were taken as the data set, Label Image software was used to label the data set, and YOLOv5 model was used to train the data set. The test results show that the method proposed in this paper can accurately identify typical foreign bodies (such as bird nests, branches and textiles) in overhead lines, and accurately mark the location of foreign bodies at different shooting distances. The training accuracy of the algorithm reaches 97.7%, and the detection accuracy is maintained at a high level, which can meet the requirements of automatic operation and maintenance inspection for overhead transmission lines.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yong Yu, Yanchao Sun, Yanlai Tang, Bowen Yin, Qi Wu, and Chong Qu "Research on identification and detection of foreign body intrusion for overhead lines", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 1315964 (13 May 2024); https://doi.org/10.1117/12.3024317
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KEYWORDS
Education and training

Inspection

Detection and tracking algorithms

Data modeling

Unmanned aerial vehicles

Evolutionary algorithms

Image processing

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