| 基于LVQ神经网络的冷轧带钢表面缺陷分类方法 |
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| 引用本文： | 吴贵芳,徐科,徐金梧.基于LVQ神经网络的冷轧带钢表面缺陷分类方法[J].北京科技大学学报,2005,27(6):732-735. |
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| 作者姓名： | 吴贵芳 徐科 徐金梧 |
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| 作者单位： | 北京科技大学机械工程学院,北京,100083 |
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| 基金项目： | 中国科学院资助项目
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国家科技攻关项目 |
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| 摘 要： | 将LVQ神经网络用于冷轧带钢表面缺陷的自动分类中,解决了以往分类方法在多噜缺陷模式类型情况下耗时多和准确率低的问题.对现场采集到的14种主要缺陷类型进行了实验.实验结果表明,基于LVQ神经网络的分类器训练与分类的时间短,在多缺陷种类分类的过程中准确率能得到保证.
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| 关 键 词： | 冷轧带钢 表面缺陷 缺陷分类 LVQ神经网络 神经网络 冷轧 带钢表面缺陷 分类方法 neural network based cold surface defects 过程 缺陷种类 时间 训练 分类器 结果 实验 缺陷类型 现场采集 问题 准确率 情况 |
| 收稿时间： | 2004-11-01 |
| 修稿时间： | 2005-01-17 |
Classification of surface defects for cold rolled strips based on LVQ neural network |
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| WU Guifang,XU Ke,XU Jinwu.Classification of surface defects for cold rolled strips based on LVQ neural network[J].Journal of University of Science and Technology Beijing,2005,27(6):732-735. |
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| Authors: | WU Guifang XU Ke XU Jinwu |
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| Institution: | Mechanical Engineering School, University of Science and Technology Beijing, Beijing 100083, China |
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| Abstract: | A new method which uses LVQ neural network in the automatic classification of surface defects for cold rolled strips was presented. The problems of long time and low accuracy in the classification of multi-defect pattern types with some traditional classification algorithms were resolved. Tested by 14 main defect types collected from online data, the results demonstrated that the method of surface defects for cold rolled strips based on LVQ neural network spent little time during training and classifying, and its accuracy could be assured on the recognition process of multi-defect pattern types. |
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| Keywords: | cold rolled strips surface defect defect classification LVQ neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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