计算机与现代化Issue(9)：67-72,6.DOI:10.3969/j.issn.1006-2475.2025.09.010
基于复杂环境的绝缘子缺陷检测
Insulator Defect Detection Based on Complex Environment
摘要
Abstract
Nowadays,drones have been widely used in power inspection.However,due to the complex background of insulator defect images,small defect sizes,and the occurrence of multiple damage situations such as flashover,self explosion,and break-age,the detection speed and accuracy are greatly limited.To address these issues,a complex environment insulator defect detec-tion method based on improved YOLOv5 is proposed.Firstly,an improved feature extraction network C2FNet is adopted to obtain richer feature information while ensuring lightweight.Secondly,the Res2Net module with multi-scale information is adopted to improve gradient propagation and training performance.Finally,a dynamic object detection head 3-DyHead with adaptive fusion is designed to dynamically adjust the network structure and parameters.The experimental results show that the average accuracy of this method has reached 94.2%,which is 4.1 percentage points higher than the original model.The precision P and recall R have increased by 3.2 percentage points and 4.0 percentage points,respectively.The average accuracy of insulator flashover,hammer,and defect has increased by 11.0 percentage points,2.0 percentage points and 6.5 percentage points.关键词
绝缘子检测/C2FNet/Res2Net/自适应融合/3-DyHeadKey words
insulator testing/C2FNet/Res2Net/adaptive fusion/3-DyHead分类
信息技术与安全科学引用本文复制引用
季星宇,黄陈蓉,姚军财,王凯,顾铭杰..基于复杂环境的绝缘子缺陷检测[J].计算机与现代化,2025,(9):67-72,6.基金项目
国家自然科学基金资助项目(61301237) （61301237）
江苏省自然科学基金面上项目(BK20201468) （BK20201468）
