现代信息科技2025，Vol.9Issue(14)：27-31,5.DOI:10.19850/j.cnki.2096-4706.2025.14.006
基于注意力机制和改进YOLOv10的PCB缺陷检测方法
PCB Defect Detection Method Based on Attention Mechanism and Improved YOLOv10
摘要
Abstract
Under the macro background of accelerating the intelligent transformation of China's manufacturing industry,especially in the wave where the country is actively advocating and vigorously promoting the development of new quality productivity,all kinds of electronic equipment have ushered in unprecedented rapid development opportunities.As a result,the reliability requirements of Printed Circuit Board(PCB),the core component of electronic products,have been raised to a new level.Any defects on the PCB surface will directly affect the overall availability and long-term stability of the electronic device.However,the traditional method of relying on manual screening is not only inefficient,but also prone to missed detection.This bottleneck problem seriously restricts the production efficiency and product quality of enterprises.In this regard,a PCB defect detection method based on improved YOLOv10 is studied,including introducing CBAM Attention Mechanism,optimizing loss function and optimizing traditional target detection head by group convolution,so as to improve the learning ability and detection accuracy of the model for fine features in PCB images.关键词
PCB/缺陷检测/YOLOv10/CBAM注意力机制/PIoU损失函数Key words
PCB/defect detection/YOLOv10/CBAM Attention Mechanism/PIoU loss function分类
信息技术与安全科学引用本文复制引用
何嘉泳,陈芳,张绮婷,陈伟迅..基于注意力机制和改进YOLOv10的PCB缺陷检测方法[J].现代信息科技,2025,9(14):27-31,5.基金项目
广州市教育局高校科研项目(2024312419) （2024312419）
