A model of image features captured by drones based on typical defects in transmission line quality

Zhenglun Chen; Xiaoquan Xie; Jiaming Liang; Tianyang Deng

doi:10.1117/12.3031080

19 July 2024 A model of image features captured by drones based on typical defects in transmission line quality

Zhenglun Chen, Xiaoquan Xie, Jiaming Liang, Tianyang Deng

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131812W (2024) https://doi.org/10.1117/12.3031080
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

The utilization of unmanned aerial vehicles (UAVs) serves as a pivotal role in the inspection of transmission lines, specifically in the detection of anomalies. This study aims to enhance the efficiency of anomaly detection by proposing an automated method using UAV inspection to identify flaws in components. Through the utilization of an end-to-end coordinate attention mechanism and a bidirectional feature pyramid network (BC-YOLO), defects in both dampers and insulators can be discerned. To overcome the challenge of background interference, researchers have integrated a coordinate attention (CA) module and implemented a bidirectional feature pyramid network (BiFPN) for effective multi-scale feature fusion. The experimental results obtained from the dataset authenticate the effectiveness of the suggested approach.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhenglun Chen, Xiaoquan Xie, Jiaming Liang, and Tianyang Deng "A model of image features captured by drones based on typical defects in transmission line quality", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131812W (19 July 2024); https://doi.org/10.1117/12.3031080

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