基于改进YOLOX的输电线路典型部件及缺陷轻量检测方法

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关键词：输电线路缺陷检测；Ghostnet;坐标注意力机制；变焦损失；实时检测DOI：10.15938/j. emc.2025.09.010中图分类号：TM75；TP391 文献标志码：A 文章编号：1007-449X（2025）09-0106-10

Abstract：Aiming at the problems of large model size and poor real-time performance in the detection of transmission line components and defects ， as well as the problems of frequent false detection and missed detection due to complex background and imbalanced samples，a light weight detection method for typical transmission line components and defects based on improved YOLOX was proposed. Firstly，Ghostnet was introduced to replace the original backbone network to achieve model lightweighting. Secondly，in order to solve the problem of frequent missed detection and false detection caused by the complex background of the transmisson line image，the coordinate attention module was embedded into both of the feature fusion network and CSPLayer structure to enhance the focus on the target area in complex background. Finally， to address the problems of the imbalance samples of transmission line components and defects and the great differences in detection difficultyof different targets，the Varifocal loss function was introduced to reduce the impact caused by the imbalance of positive and negative samples，and improve the training intensity of dificult-to-classify targets to reduce false detection and missed detection.The experimental result shows that the average accuracy of the proposed method in the detection of transmission line components and defects is increased by 2.67% ，the model size is reduced by 33.01% ，and the reasoning speed is 19.61 ms/piece， which can satisfy the requirements of UAV lightweight and high-precision power real-time inspection.

Keywords：transmission line defect detection；Ghostnet；coordinate atention；varifocal loss；realtime detection

0引言

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