| 基于支持向量机的机械故障多类分类研究 |
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| 引用本文： | 刘刚. 基于支持向量机的机械故障多类分类研究[J]. 机械管理开发, 2009, 24(4): 8-10,13 |
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| 作者姓名： | 刘刚 |
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| 作者单位： | 黑龙江省齐齐哈尔矿产勘查开发总院,黑龙江,齐齐哈尔,161006 |
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| 摘 要： | 对基于支持向量机的多类分类故障诊断方法进行了研究.采用9频段幅值谱作为分类器的特征输入.比较了现有常用的几种支持向量机多分类方法:一对一法、一对多法、导向无环图法.试验结果表明导向无环图法耗时短、分类精度更高,更适合应用于机械多分类故障诊断研究.
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| 关 键 词： | 故障诊断 支持向量 多类分类 |
Research on Machine Fault Pattern Classification Based on Support Vector Machine |
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| LIU Gang. Research on Machine Fault Pattern Classification Based on Support Vector Machine[J]. Mechanical Management and Development, 2009, 24(4): 8-10,13 |
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| Authors: | LIU Gang |
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| Affiliation: | HeiLongjiang Province Qiqihaer Mineral Perambulation and Exploitation general academy;Qiqihaer 161006;China |
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| Abstract: | This paper studies multi-class problem of machine fault diagnosis based on vector machine.9 segments of frequency spectrum is used as the input of SVM multiple classifier Three existing multi-class methods of SVM: one-vs-one,one-vs-all,Directed Acyclic Graph(DAG) is compared to test.Cross validation is use to optimize the parameters of SVM.The result indicates that DAGSVM has fewer time resume and higher classification precision than the other methods. |
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| Keywords: | Fault Diagnosis Support Vector Machine Multiple classifications |
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