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http://dx.doi.org/10.5391/JKIIS.2010.20.3.380

Induction Motor Diagnosis System by Effective Frequency Selection and Linear Discriminant Analysis  

Lee, Dae-Jong (충북대학교 제어로봇공학과 컴퓨터정보통신연구소)
Cho, Jae-Hoon (충북대학교 제어로봇공학과 컴퓨터정보통신연구소)
Yun, Jong-Hwan (충북대학교 제어로봇공학과 컴퓨터정보통신연구소)
Chun, Myung-Geun (충북대학교 제어로봇공학과 컴퓨터정보통신연구소)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.20, no.3, 2010 , pp. 380-387 More about this Journal
Abstract
For the fault diagnosis of three-phase induction motors, we propose a diagnosis algorithm based on mutual information and linear discriminant analysis (LDA). The experimental unit consists of machinery module for induction motor drive and data acquisition module to obtain the fault signal. As the first step for diagnosis procedure, DFT is performed to transform the acquired current signal into frequency domain. And then, frequency components are selected according to discriminate order calculated by mutual information As the next step, feature extraction is performed by LDA, and then diagnosis is evaluated by k-NN classifier. The results to verify the usability of the proposed algorithm showed better performance than various conventional methods.
Keywords
Fault Diagnosis; LDA; Mutual information; Induction motor;
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