Bearing fault detection of induction motor using wavelet and Support Vector Machines (SVMs)

被引:372
|
作者
Konar, P. [1 ]
Chattopadhyay, P. [1 ]
机构
[1] Bengal Engn & Sci Univ, Dept Elect Engn, Howrah 711103, W Bengal, India
关键词
Condition monitoring; Induction motor; Bearing fault; Continuous wavelet transform (CWT); Support Vector Machine (SVM); SIGNATURE ANALYSIS; DIAGNOSIS; SYSTEM;
D O I
10.1016/j.asoc.2011.03.014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Condition monitoring of induction motors is a fast emerging technology in the field of electrical equipment maintenance and has attracted more and more attention worldwide as the number of unexpected failure of a critical system can be avoided. Keeping this in mind a bearing fault detection scheme of three-phase induction motor has been attempted. In the present study, Support Vector Machine (SVM) is used along with continuous wavelet transform (CWT), an advanced signal-processing tool, to analyze the frame vibrations during start-up. CWT has not been widely applied in the field of condition monitoring although much better results can been obtained compared to the widely used DWT based techniques. The encouraging results obtained from the present analysis is hoped to set up a base for condition monitoring technique of induction motor which will be simple, fast and overcome the limitations of traditional data-based models/techniques. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:4203 / 4211
页数:9
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