| 基于支持向量机的故障诊断方法 |
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| 引用本文： | 王华忠,张雪申,俞金寿. 基于支持向量机的故障诊断方法[J]. 华东理工大学学报(自然科学版), 2004, 30(2): 179-182 |
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| 作者姓名： | 王华忠 张雪申 俞金寿 |
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| 作者单位： | 华东理工大学自动化研究所,上海,200237;华东理工大学自动化研究所,上海,200237;华东理工大学自动化研究所,上海,200237 |
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| 摘 要： | 提出了基于支持向量机的故障诊断方法和步骤。诊断实例表明，与神经网络故障诊断方法相比，诊断小样本分析的支持向量机故障诊断方法具有分类能力强、推广能力好的特点。
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| 关 键 词： | 支持向量机 故障诊断 统计学习理论 |
| 文章编号： | 1006-3080(2004)02-0179-04 |
| 修稿时间： | 2003-06-02 |
Fault Diagnosis Based on Support Vector Machine |
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| WANG Hua-zhong,ZHANG Xie-shen,YU Jin-shou. Fault Diagnosis Based on Support Vector Machine[J]. Journal of East China University of Science and Technology, 2004, 30(2): 179-182 |
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| Authors: | WANG Hua-zhong ZHANG Xie-shen YU Jin-shou |
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| Affiliation: | WANG Hua-zhong,ZHANG Xie-shen,YU Jin-shou~* |
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| Abstract: | Fault diagnosis method based on SVM is proposed in this paper. The research shows that the method suggested features higher performance on classification and generalization ability and shorter training time over the methods based on artificial neural networks, especially for small samples. |
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| Keywords: | support vector machine fault diagnosis statistical learning theory |
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