Gear fault diagnosis based on rough set and support vector machine

被引：0

作者：

Tian Huifang ^{[1
]}

Sun Shanxia ^{[1
]}

机构：

[1] Wuhan Univ Technol, Sch Mech & Elect Engn, Wuhan 430070, Peoples R China

来源：

1st International Symposium on Digital Manufacture, Vols 1-3 | 2006年

关键词：

rough set; support vector machine; fault diagnosis; multi-classifier;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

By introducing Rough Set Theory and the principle of Support vector machine, a gear fault diagnosis method based on them is proposed. Firstly, diagnostic decision-making is reduced based on rough set theory, and the noise and redundancy in the sample are removed, then, according to the chosen reduction, a support vector machine multi-classifier is designed for gear fault diagnosis. Therefore, SVM' training data can be reduced and running speed can quicken. Test shows its accuracy and efficiency of gear fault diagnosis.

引用

页码：1046 / 1051

页数：6

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