Fault Classification Model of Rotor Based on Support Vector Machine

被引：0
|
作者：
Niu, Wei [1 ]
Wang, GuoQing [2 ]
Zhai, ZhengJun [1 ]
Cheng, Juan [3 ]
机构：
[1] Northwestern Polytech Univ, Coll Comp, Xian 710072, Peoples R China
[2] Chinese Aeronaut Radio Elect Res Inst, Shanghai 200233, Peoples R China
[3] Xian Inst Appl Opt, Xian 710065, Peoples R China
来源：
MECHANICAL, MATERIALS AND MANUFACTURING ENGINEERING, PTS 1-3 | 2011年 / 66-68卷
关键词：
support vector machine; fault diagnosis; wavelet packet; DDAG;
D O I：
10.4028/www.scientific.net/AMM.66-68.1982
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The vibration signals of rotating machinery in operation consist of plenty of information about its running condition, and extraction and identification of fault signals in the process of speed change are necessary for the fault diagnosis of rotating machinery. This paper improves DDAG classification method and proposes a new fault diagnosis model based on support vector machine to solve the problem of restricting the rotating machinery fault intelligent diagnosis due to the lack of fault data samples. The testing results demonstrate that the model has good classification precision and can correctly diagnose faults.
引用
收藏
页码：1982 / +
页数：2
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