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基于改进的RT-DETR小目标PCB缺陷检测

张宗旋 孙旋

现代电子技术2026,Vol.49Issue(13):119-127,9.
现代电子技术2026,Vol.49Issue(13):119-127,9.DOI:10.16652/j.issn.1004-373X.2026.13.018

基于改进的RT-DETR小目标PCB缺陷检测

PCB small object defect detection based on improved RT-DETR

张宗旋 1孙旋2

作者信息

  • 1. 广西高校先进制造与自动化技术重点实验室,广西 桂林 541006||桂林理工大学 机械与控制工程学院,广西 桂林 541006
  • 2. 广西高校先进制造与自动化技术重点实验室,广西 桂林 541006||桂林理工大学 机械与控制工程学院,广西 桂林 541006||广西特种工程装备与控制重点实验室,广西 桂林 541004
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摘要

Abstract

An improved RT-DETR algorithm is proposed to tackle common challenges in printed circuit board(PCB)defect detection,including missed detections,false detections,and the low detection rate of tiny defects.Firstly,a multi-scale feature edge information fusion(MSFEIF)module is designed in the backbone network to enhance the network 's ability to extract multi-scale edge features and achieve global propagation of edge information.Additionally,an efficient adaptive attention(EAA)mechanism is introduced to the original AIFI module,and an AIFI-EAA scale interaction module is constructed.This modification reduces computational complexity,speeds up inference,and improves the detection accuracy of the model.Furthermore,combining the advantages of RepC3 and RmtBlock structures,a new RmtBlockC3 module is designed to effectively enhance the spatial modeling and global perception capabilities of the network.Finally,by integrating the Inner-IoU concept with the MPDIoU loss function,the matching accuracy of bounding box regression and keypoint localization accuracy is improved without increasing model parameters,so as to further enhance the detection performance.Experiments on the PCB defect dataset demonstrate that the improved model achieves superior performance compared to the baseline RT-DETR.Specifically,its precision increases by 4.3%,its recall rate by 3.3%,and its mean average precision(mAP@0.5)by 3.5%.These results indicate that the proposed algorithm holds high value for the practical application of small object defect detection in PCB inspection.

关键词

小目标检测/RT-DETR/缺陷检测/PCB/特征融合/Transformer

Key words

small object detection/RT-DETR/defect detection/PCB/feature fusion/Transformer

分类

信息技术与安全科学

引用本文复制引用

张宗旋,孙旋..基于改进的RT-DETR小目标PCB缺陷检测[J].现代电子技术,2026,49(13):119-127,9.

基金项目

广西特种工程装备与控制重点实验室(桂林航天工业学院)开放基金(2411KFYB02) (桂林航天工业学院)

现代电子技术

1004-373X

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