计算机与数字工程2025，Vol.53Issue(1)：77-83,7.DOI:10.3969/j.issn.1672-9722.2025.01.016
基于YOLOv5的汽车安全系统导向爪表面缺陷检测应用研究
Application Research on Surface Defect Detection of Guide Claw of Automobile Safety System Based on YOLOv5
摘要
Abstract
Aiming at the stamping part of the guide claw of the automobile safety system,a target detection algorithm based on YOLOv5 is proposed to detect the surface defects of the guide claw of the automobile safety system.Firstly,the original data is fil-tered to remove invalid data.Secondly,to solve the problem of unbalanced samples,some data are amplified.Then the LabelImg tool is used to label the expanded data set.Then the labeled data set is put into the model perform training.Finally the optimal weights obtained from training are used for testing.Experiments show that the detection effect of YOLOv5 is significantly better than the three target detection models of Faster R-CNN,SSD,and RetinaNet.Its mAP can reach 98.4%,and the average detection time is 6.2 ms.The defect detection method based on YOLOv5 can meet the detection speed and accuracy requirements of the actual pro-duction line,and has important guiding significance for the defect detection of stamping parts.关键词
冲压零件/汽车安全系统导向爪/YOLOv5/目标检测Key words
stamping parts/guide claw of automobile safety system/YOLOv5/target detection分类
交通工程引用本文复制引用
张倩倩,何仕荣,赵士雨,张浩洋..基于YOLOv5的汽车安全系统导向爪表面缺陷检测应用研究[J].计算机与数字工程,2025,53(1):77-83,7.基金项目
上海市自然科学基金面上项目(编号:20ZR1438000) （编号:20ZR1438000）
上海市科学技术委员会项目(编号:19060502300)资助. （编号:19060502300）
