Research on defect recognition method of transmission line insulators

Yi Zhu; Xianwen Zeng

doi:10.1117/12.3008690

27 October 2023 Research on defect recognition method of transmission line insulators

Yi Zhu, Xianwen Zeng

Proceedings Volume 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023); 1292212 (2023) https://doi.org/10.1117/12.3008690
Event: Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 2023, Xiamen, China

Abstract

For the detect recognition of transmission line insulators, there are some problems for the traditional fault recognition algorithms, such as false detection, omission of detection, low and slow recognition rate. Compared with the traditional convolutional neural networks, vector is used by the capsule network as the input. Each sub-structure of the capsule makes the details highly fidelity in the original graph, which can effectively identify the defective insulator image. Therefore, a detect recognition method based on improved capsule network and YOLO-V5 is proposed in this paper. Experimental results demonstrate that the algorithm performs well and meets the requirements for inspecting insulators.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yi Zhu and Xianwen Zeng "Research on defect recognition method of transmission line insulators", Proc. SPIE 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 1292212 (27 October 2023); https://doi.org/10.1117/12.3008690

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