广东工业大学学报 ›› 2016, Vol. 33 ›› Issue (03): 65-69.doi: 10.3969/j.issn.1007-7162.2016.03.012

• 综合研究 • 上一篇    下一篇

基于机器视觉的贴片引脚焊接缺陷检测

戴知圣, 潘晴, 常桂林, 陈健刚   

  1. 广东工业大学 信息工程学院,广东 广州 510006
  • 收稿日期:2015-08-10 出版日期:2016-05-19 发布日期:2016-05-19
  • 通信作者: 潘晴(1975-),男,副教授,主要研究方向为图像处理、模式识别,E-mail:12936434@qq.com
  • 作者简介:戴知圣(1988-),男,硕士研究生,主要研究方向为图像处理、机器视觉.
  • 基金资助:

    国家自然科学基金资助项目(61202268)

Detection of Welding Defects in SMT Chip Pins Based on Machine Vision

Dai Zhi-sheng, Pan Qing, Chang Gui-lin, Chen Jian-gang   

  1. School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2015-08-10 Online:2016-05-19 Published:2016-05-19

摘要:

针对印刷电路板(Printed Circuit Board,PCB)中贴片元件引脚焊接在线检测问题,提出一种基于机器视觉的引脚焊接缺陷检测的算法.通过对引脚区域进行特征提取,综合采用面积法、连通域法质心法,实现对贴片引脚处附焊球、引脚桥接、缺焊及合格情况进行自动识别.提出了基于统计方法的参数阈值自适应修正的方法,有效解决固定阈值的局限性问题,使算法能够适用于不同光照强度的环境.实验结果表明,该算法对PCB中贴片元件引脚焊接缺陷检测的识别具有较高的准确性.

关键词: 贴片引脚; 焊接检测; 特征提取; 机器视觉

Abstract:

For the problem of SMT components pin welding online detection in PCB, a pin welding defect detection based on machine vision algorithm is proposed. To achieve automatic identification, this paper extracts the features of pin, applies area method and the connected domain method comprehensively to recognize patch pin attached solder ball, foot bridge, lack of welding and qualified products. Therefore, an approach of adaptive correction of parameter threshold based on statistical method is put forward, which can solve the problem of limitation of the fixed threshold effectively and make the algorithm apply to the environment with different light intensity. The experimental results show that the algorithm of PCB in detecting welding defects in SMT chip pins has higher accuracy.

Key words: pins of SMT; welding detection; feature extraction; machine vision

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