Neural Network-Based Inspecting Method of PCB Solder Joint

Journal of South China University of Technology (Natural Science Edition) ›› 2008, Vol. 36 ›› Issue (5): 135-139.

• Electronics, Communication & Automation Technology • Previous Articles Next Articles

Neural Network-Based Inspecting Method of PCB Solder Joint

Lu Sheng-lin Zhang Xian-min Kuang Yong-cong

School of Mechanical Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China

Received:2007-11-08 Revised:2008-01-03 Online:2008-05-25 Published:2008-05-25
Contact: 卢盛林（1980-），男，博士生，主要从事基于图像的电路板检测技术研究． E-mail:joolu@163．com
About author:卢盛林（1980-），男，博士生，主要从事基于图像的电路板检测技术研究．
Supported by:
粤港关键领域重点突破招标项目（东莞专项20061682）;广东省、教育部产学研结合项目（2006D930304001）

Abstract

Abstract:

In order to overcome the error alarming and unintelligence of the automatic optical inspection（AOI） system for the solder joint inspection,a new inspecting method based on neural network is proposed.First,an entropy-based multi-threshold algorithm is adopted to automatically segment the image and to extract the solder joints.Second,a series of features of solder joints is defined and are selected according to the experimental results.Thirdly,a BP neural network is established for the solder joints classification.The high accuracy of the proposed method is verified by experiments.

Key words: automatic optical inspection, printed circuit-board, neural network, machine vision

Lu Sheng-lin Zhang Xian-min Kuang Yong-cong. Neural Network-Based Inspecting Method of PCB Solder Joint[J]. Journal of South China University of Technology (Natural Science Edition), 2008, 36(5): 135-139.

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Neural Network-Based Inspecting Method of PCB Solder Joint

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