A pattern matching and parameter self-adaptive based PCB solder joint inspection algorithm

Wu Fu-pei; Yong-cong Kuang; Xian-Min ZHANG; Gaofei Ou-yang

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A pattern matching and parameter self-adaptive based PCB solder joint inspection algorithm

Article | 更新时间：2020-08-12

- A pattern matching and parameter self-adaptive based PCB solder joint inspection algorithm
- Optics and Precision Engineering Vol. 17, Issue 10, Pages: 2586-2593(2009)
- 作者机构：
  
  华南理工大学机械与汽车工程学院2. 华南理工大学机械工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP274+.5;TP391.4
- Received：24 September 2008，
  
  Revised：16 December 2008，
  
  Published Online：20 October 2009，
  
  Published：20 October 2009
- 稿件说明：
移动端阅览
吴福培,邝泳聪,张宪民,欧阳高飞. 基于模式匹配及其参数自适应的PCB焊点检测算法[J]. 光学精密工程, 2009,17(10):2586-2593

Wu Fu-pei, Yong-cong Kuang, Xian-Min ZHANG, et al. A pattern matching and parameter self-adaptive based PCB solder joint inspection algorithm[J]. Optics and precision engineering, 2009, 17(10): 2586-2593.
吴福培,邝泳聪,张宪民,欧阳高飞. 基于模式匹配及其参数自适应的PCB焊点检测算法[J]. 光学精密工程, 2009,17(10):2586-2593 DOI：

Wu Fu-pei, Yong-cong Kuang, Xian-Min ZHANG, et al. A pattern matching and parameter self-adaptive based PCB solder joint inspection algorithm[J]. Optics and precision engineering, 2009, 17(10): 2586-2593. DOI：

摘要

为了提高在线自动光学检测(AOI)系统检测印刷电路板(PCB)焊点的准确率和速度，对PCB焊点进行了研究。通过研究由特定结构光源和3CCD彩色相机获取的PCB焊点图像，基于常见的良品、多锡、少锡、假焊等焊点类型，提取焊点图像关键子区域的面积特征，在此基础上，建立了五种焊点类型的特征矩阵模型，并根据同类焊点相似程度最大为原则设计了检测焊点的模式匹配算法。此外，本文还给出了一种参数自适应方法对各检查项所用到的阀值参数进行学习与校正。在实验研究中，对含有1040个Chip焊点的PCB进行了检测，结果显示本文所提算法对焊点检测的准确率可达96.5%，检测所用时间为9秒。研究结果表明，本文算法具有较高检测准确率和检测速度。

Abstract

In order to improve the inspection success rate and velocity of the in-line Automated Optical Inspection (AOI) system of Printed Circuit Boards (PCBs)

the solder joints of a PCB are studied. The solder joint images are acquired by a structure illuminator and a 3-CCD color camera. Based on the images

the area features of the conventional kinds of the PCB solder joints such as good

excessive

poor

pseudo are extracted with respect to the key sub-region in a solder joint. Five kinds of feature matrixes models of solder joints are presented. A pattern matching algorithm for inspecting the solder joint is developed by maximum the similarity of the same kind of solder joins. To solve the problem of the thresholds determined by experience

a parameter self-adaptive learning strategy is presented. Finally

a 1040 chip solder joints PCB is inspected. Experimental results show that the success rate is up to 96.5% and the inspection time is 9 seconds using the proposed algorithm

which indicates that the proposed algorithm can achieve both high success rate and inspecting velocity.

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Related Institution

School of Mechanical and Automotive Engineering, South China University of Technology

Department of Mechatronic Engineering, Shantou University

School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, China

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