航天器环境工程2025，Vol.42Issue(5)：557-565,9.DOI:10.12126/see.2025063
基于ST-ResNet的印制电路板红外热成像故障诊断方法
A fault diagnosis method for printed circuit boards based on ST-ResNet and infrared thermography
摘要
Abstract
Infrared thermography-based fault diagnosis of printed circuit boards(PCBs)is gaining attention in field applications such as emergency repairs and equipment inspections due to its rapid detection,simple operation,and equipment versatility.However,existing methods often require strict image acquisition conditions and are not suitable for portable devices.To overcome these limitations,a novel fault diagnosis method for PCBs using portable devices is proposed,based on a convolutional neural network(CNN)for infrared thermogram classification.A pre-trained Residual Neural Network(ResNet)was employed as the backbone to automatically extract diagnostic features from the images.In addition,a Spatial Transformer Network(STN)was integrated at the input stage to enhance the network's robustness to viewpoint variations,thereby reducing the dependence on strict imaging conditions.Five-fold cross-validation was performed on a self-built dataset containing multi-view images.The results demonstrated that the proposed method achieved an average accuracy of 93%.This study provides a new approach for the development of portable infrared fault diagnosis devices for PCBs.关键词
故障诊断/印制电路板/红外热成像/卷积神经网络/特征提取Key words
fault diagnosis/printed circuit board(PCB)/infrared thermography/convolutional neural network(CNN)/feature extraction分类
信息技术与安全科学引用本文复制引用
李昊,黄首清,许庶,方舟,余溢方,丁亮..基于ST-ResNet的印制电路板红外热成像故障诊断方法[J].航天器环境工程,2025,42(5):557-565,9.基金项目
国家国防科工局技术基础科研计划项目(编号:JSZL2021601B001-38) （编号:JSZL2021601B001-38）
