计算机科学与探索2025，Vol.19Issue(4)：901-915,15.DOI:10.3778/j.issn.1673-9418.2409061
基于机器视觉的PCB缺陷检测算法研究综述
Review of PCB Defect Detection Algorithm Based on Machine Vision
摘要
Abstract
Printed circuit board(PCB)as a core component of electronic products,its quality directly affects the reliability of the product.As electronic products move toward lighter,thinner,and more sophisticated,machine vision-based PCB defect detection faces challenges such as the difficulty of detecting tiny defects.In order to further study the PCB defect detection technology,the algorithms of each stage are discussed in detail according to the development history.Firstly,the main challenges in the field are pointed out,and traditional PCB defect detection methods and their limitations are intro-duced.Then,from the perspective of traditional machine learning and deep learning,this paper systematically reviews the PCB defect detection methods and their advantages and disadvantages in recent years.Next,this paper summarizes the commonly used evaluation indicators and mainstream datasets of PCB defect detection algorithms,compares the perfor-mance of the latest research methods on PCB-Defect,DeeP-PCB and HRIPCB datasets in the past three years,and analyzes the reasons for the differences.Finally,based on the current situation and the problems to be solved,the future develop-ment trend is prospected.关键词
印刷电路板(PCB)/缺陷检测/机器视觉/机器学习/深度学习Key words
printed circuit board(PCB)/defect detection/machine vision/machine learning/deep learning分类
计算机与自动化引用本文复制引用
杨思念,曹立佳,杨洋,郭川东..基于机器视觉的PCB缺陷检测算法研究综述[J].计算机科学与探索,2025,19(4):901-915,15.基金项目
中国高校产学研创新基金(2021ZYA11002) （2021ZYA11002）
四川轻化工大学科研创新团队计划(SUSE652A011) （SUSE652A011）
四川轻化工大学自然科学基金(2024RC03) （2024RC03）
四川轻化工大学研究生创新基金(Y2024119) （Y2024119）
企业信息化与物联网测控技术四川省高校重点实验室开放基金(2024WZY01).This work was supported by the Industry-University-Research Innovation Fund for Chinese Universities(2021ZYA11002),the Re-search Innovation Team Program of Sichuan University of Science&Engineering(SUSE652A011),the Natural Science Foundation of Sichuan University of Science&Engineering(2024RC03),the Graduate Innovation Fund of Sichuan University of Science&Engineering(Y2024119),and the Opening Fund of Key Laboratory of Higher Education of Sichuan Province for Enterprise Informationalization and Internet of Things(2024WZY01). （2024WZY01）
