| 基于BP神经网络的焊点自动光学检测 |
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| 引用本文： | 王小彬,顾济华,杨勇,周皓,王永彬,许亚娟. 基于BP神经网络的焊点自动光学检测[J]. 光学技术, 2009, 35(6) |
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| 作者姓名： | 王小彬 顾济华 杨勇 周皓 王永彬 许亚娟 |
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| 作者单位： | 教育部现代光学技术重点实验室,江苏,苏州,215006;苏州大学,物理科学与技术学院,江苏,苏州,215006;苏州大学,物理科学与技术学院,江苏,苏州,215006;恭硕电子科技(上海)有限公司,上海,201319 |
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| 摘 要： | 提出了一种新的表面组装焊点的自动光学检测分类方法。采用单层环形光源获取焊点图像,并根据归一化分割曲线方程将焊点图像分成四部分,分别提取其特征。使用BP神经网络将焊点按照锡量多少分成三类:少锡,容许和多锡。实验结果证明该方法分类正确率达到了99.2%,具有较高的实用价值。
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| 关 键 词： | 自动光学检测 焊点检查 表面组装技术 BP神经网络 模式识别 |
Automatic optical inspection for solder joints based on BP neural network |
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| WANG Xiao-bin,GU Ji-hua,YANG Yong,ZHOU Hao,WANG Yong-bin,XU Ya-juan. Automatic optical inspection for solder joints based on BP neural network[J]. Optical Technique, 2009, 35(6) |
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| Authors: | WANG Xiao-bin GU Ji-hua YANG Yong ZHOU Hao WANG Yong-bin XU Ya-juan |
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| Abstract: | A neural network based on automatic optical inspection system for the diagnosis of solder joints defects on printed circuits boards assembled in surface mounting technology(SMT) is presented.The diagnosis is handled as a pattern recognition problem with a back-propagation(BP) neural network approach.Four features are extracted from the solder joints image,which are captured by using only one layer of tiered light.Three types of solder joints have been classified according to the features: insufficient,accep... |
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| Keywords: | automatic optical inspection solder joints inspection surface mounting technology artificial neural network pattern recognition |
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