基于改进YOLOv8n的PCBA外观缺陷检测

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中图分类号：TN911.73-34 文献标识码：A 文章编号：1004-373X（2025）17-0176-05

DOI：10.16652/j.issn.1004-373x.2025.17.026 引用格式：，.基于改进YOLOv8n的PCBA外观缺陷检测[J].现代电子技术，2025，48（17）：：176-180.

PCBA surfacedefectdetection based on improved YOLOv8n

ZHOU Zhiwei，HAN Bin

SchoolofInformationandControlEngineering，SouthwestUniversityofScienceandTechnologyMianyang6Chir

Abstract：Thedesignsof modernPCBA（printed circuit boardasembly）arecomplex，andtheirdensitiesare getting higher andhigher.Thedistancesbetweencircuitsandcomponentsaregetingcloser.Thishigh-densitylayoutresultsinmoretypesand smallrrangesofdefectsonPCBA，increasing thedificultyof defectdetection.ImprovingtheLSKmoduleinYOLOv8nby combininglargekernelandsmallkernelconvolutionscancapturefeaturesofdiferentscales，therebyimprovingthereliabilityof appearance defect detection.Inviewof this，aPCBAappearance defectdetection method basedonimproved YOLOv8nis studied.FirstlyeferigtotenetworkstructureofSlim-neck，theetworkstructureofNeckisimproedtoachievelighweight. Secondly，theintroductionofLSK modulesenhances themeanaverage precision （mAP）reduced due tothe lightweightnetwork structure.Then，byintroducingtheSEmodule，thenetworkstructureoftheHeadisimprovedtofurtherenhancethedetection performanceof themodel.Finally，theMPDIUlossfunctionisintroduced toenhance theabilityofsmallojectdetection.The experimentalresultsshowthatthemAPoftheimproved modelproposed inthispaperreaches95.2%onthePCBAappearance defect dataset， increasing by 3.1% in comparison with that of YOLOv8n. The validity of the proposed model is verified.

Keywords：PCBA;appearance inspection;defect detection; improved YOLOv8n; lossfunction;lightweightnetwork

0 引言

印制电路板（PCB）作为电子元器件安装和电路电气连接的载体，是各类型电子产品的重要组成部分，提高其生产制造水平，对于计算机、消费电子、通信设备等行业发展有着至关重要的作用。（剩余5216字）