| 基于BP神经网络的钢球表面缺陷识别 |
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| 引用本文： | 陈涛,刘献礼,吉举正,周洪玉.基于BP神经网络的钢球表面缺陷识别[J].机械工程师,2010(7):56-57. |
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| 作者姓名： | 陈涛 刘献礼 吉举正 周洪玉 |
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| 作者单位： | 1. 哈尔滨理工大学,哈尔滨,150080
2. 哈尔滨电机厂,哈尔滨,150040 |
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| 基金项目： | 黑龙江省教育厅科学技术研究项目 |
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| 摘 要： | 采用灰度共生矩阵为基础的纹理特征计算方法，对钢球表面图像进行特征参数提取，应用基于BP神经网络的图像特征模式识别方法，实现了对钢球表面不同种类缺陷的准确识别，实验结果表明，该方法能够对钢球表面缺陷进行有效地分类识别。
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| 关 键 词： | 钢球 表面缺陷 灰度共生矩阵 BP神经网络 |
Discernment of Steel Ball Surface Defect Based on BP Neural Network |
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| CHEN Tao,LIU Xian-li,JI Ju-zheng,ZHOU Hong-yu.Discernment of Steel Ball Surface Defect Based on BP Neural Network[J].Mechanical Engineer,2010(7):56-57. |
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| Authors: | CHEN Tao LIU Xian-li JI Ju-zheng ZHOU Hong-yu |
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| Affiliation: | ( l.Harbin University of Science and Technology. Harbin 150080m China; 2.Harbin Electric Machinery Co. Ltd, Harbin 150040, China) |
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| Abstract: | Feature parameters of steel ball surface images has been acquired by using the grey level intergrowth matrix. Based on BP neural network , the discernment method has predicted steel ball surface defects more accurately. Experimenl results show that the method has good discernment performance. |
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| Keywords: | rolling bearings： surface defect grey level intergrowth matrix BP neural network |
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