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基于改进YOLOv5s的绝缘子定位检测及红外故障识别

任毅 王鹏 倪彬 顾鹏 汪易萱 刘凯波

测控技术2024,Vol.43Issue(8):7-14,22,9.
测控技术2024,Vol.43Issue(8):7-14,22,9.DOI:10.19708/j.ckjs.2024.08.304

基于改进YOLOv5s的绝缘子定位检测及红外故障识别

Insulator Positioning Detection and Infrared Fault Recognition Based on Improved YOLOv5s

任毅 1王鹏 1倪彬 1顾鹏 1汪易萱 1刘凯波2

作者信息

  • 1. 国网新疆电力有限公司巴州供电公司,新疆库尔勒 841000
  • 2. 华北电力大学,北京 102206
  • 折叠

摘要

Abstract

In insulator positioning detection and thermal faults recognition,due to severe background interfer-ence in insulator infrared images,the average recognition accuracy is low.In order to achieve precise position and detect of insulator position and improve the reliability and accuracy of identifying its thermal faults,an im-proved insulator positioning detection and infrared faults recognition method based on YOLOv5s is proposed.Firstly,a new structure C3GC is proposed by integrating the global context attention mechanism with the C3 structure of YOLOv5s Backbone,which enhances the ability of the model to extract features and reduces its a-mount of calculation.Secondly,replacing the loss function with VariFocal Loss,the recall rate of the model is improved,which can reduce the problems of missed detections of model.Finally,by introducing transposed con-volution and dynamically learning the parameters that need to be supplemented,the loss of features of the mod-el during sampling process is reduced.The experimental and testing results show that compared with the origi-nal YOLOv5s,the improved method improves positioning accuracy by 1.3%,detection accuracy for fault points by 4%,average accuracy by 2.8%,and both accuracy and recall rate is improved.

关键词

YOLOv5s/红外图像/定位检测/故障检测/热故障

Key words

YOLOv5s/infrared images/positioning detection/fault detection/thermal faults

分类

计算机与自动化

引用本文复制引用

任毅,王鹏,倪彬,顾鹏,汪易萱,刘凯波..基于改进YOLOv5s的绝缘子定位检测及红外故障识别[J].测控技术,2024,43(8):7-14,22,9.

基金项目

国网新疆电力有限公司科技项目(5230BD230003) (5230BD230003)

测控技术

OACSTPCD

1000-8829

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