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基于改进YOLOv8的印刷电路板缺陷检测方法研究

金强山 冯光 田纪亚 张一川

现代信息科技2024,Vol.8Issue(24):26-30,5.
现代信息科技2024,Vol.8Issue(24):26-30,5.DOI:10.19850/j.cnki.2096-4706.2024.24.006

基于改进YOLOv8的印刷电路板缺陷检测方法研究

Research on Defect Detection Method of Printed Circuit Board Based on Improved Yolov8

金强山 1冯光 1田纪亚 1张一川1

作者信息

  • 1. 新疆理工学院,新疆 阿克苏 843100
  • 折叠

摘要

Abstract

In order to solve the problem of low detection accuracy and low detection efficiency of small target defects on the surface of the Printed Circuit Board,this paper proposes the Printed Circuit Board defect detection method based on improved YOLOv8.The Simplified Spatial Pyramid Pooling Fast module is used in the YOLOv8 model backbone network,and the Rectified Linear Unit activation function is used to effectively improve the detection efficiency.Using the improved Bottleneck Attention Module,the channel attention branch and the spatial attention branch are used to make the model have a strong representation ability to obtain feature information and improve the detection accuracy.The loss function is improved,and the WIoU loss function is constructed to reduce the influence of geometric factors when the anchor box coincides with the target box.On the defect data set of Printed Circuit Board,the detection accuracy mAP@0.5 value of the network model reaches 90.2%,which is 5.7%higher than that of the original network model,which is of great significance to the defect detection of Printed Circuit Board.

关键词

YOLOv8/印刷电路板/缺陷检测

Key words

YOLOv8/Printed Circuit Board/defect detection

分类

信息技术与安全科学

引用本文复制引用

金强山,冯光,田纪亚,张一川..基于改进YOLOv8的印刷电路板缺陷检测方法研究[J].现代信息科技,2024,8(24):26-30,5.

基金项目

新疆理工学院校级自科科研项目(ZY202107) (ZY202107)

现代信息科技

2096-4706

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