长春工程学院学报（自然科学版）2026，Vol.27Issue(1)：75-83,9.DOI:10.3969/j.issn.1009-8984.2026.01.012
基于改进YOLOv10n模型的高压输电线路异物检测方法
Foreign object detection method for high-voltage transmission lines based on improved YOLOv10n model
摘要
Abstract
Addressing the issues of complex backgrounds and low detection accuracy in foreign object detec-tion for high-voltage transmission lines in real-world environments,this paper proposed an improved YOLOv10n detection model,YOLOv10n-OMW.Firstly,an all-dimensional dynamic convolution(ODConv)was introduced into the backbone network,combining channel attention,spatial attention,and dynamic con-volution kernel selection mechanism to dynamically extract foreign object features.Secondly,a multi-scale enhanced spatial attention mechanism(MES Attention)was designed to extract spatial features through multi-scale adaptive pooling,suppress complex background interference,and highlight key areas of foreign objects.Finally,the Wise-IoU(WIoU)loss function was introduced to replace the original Complete Inter-section over Union(CIoU)loss function,enhancing the overall performance of the model.Experimental re-sults show that the improved YOLOv10n-OMW model achieves a detection accuracy of 98.0%,an im-provement of 3.9%compared to YOLOv10n,and demonstrates superior performance in complex back-grounds,providing a technical reference for intelligent power inspection.关键词
异物检测/YOLOv10/注意力机制/损失函数/卷积模块Key words
foreign object detection/YOLOv10/attention mechanism/loss function/convolution module分类
信息技术与安全科学引用本文复制引用
李鑫,赵佳..基于改进YOLOv10n模型的高压输电线路异物检测方法[J].长春工程学院学报（自然科学版）,2026,27(1):75-83,9.基金项目
吉林省科技发展计划杰出青年人才项目(20240602004RC) （20240602004RC）
