|Table of Contents|

 Diagnosis of broken rotor bars in squirrel cage induction motors
using Morlet wavelet demodulation techniaues
(PDF)

[ISSN:1007-449X/CN:23-1 408/TM]

Issue:
2014年07
Page:
31-36
Research Field:
Publishing date:

Info

Title:
 Diagnosis of broken rotor bars in squirrel cage induction motors
using Morlet wavelet demodulation techniaues
Author(s):
 ZHU Hong-yu 1234
HU Jing-tao 1
2’3GAO Lei’12’3
HUANG Hao 1
3
 1. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016,China
2. University of Chinese Academy of Sciences, Beijing 100049,China;
3. CAS Key Laboratory of Networked Control System, Shenyang 110016,China;
4. School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114051,China
Keywords:
 Key words:induction motorsfault diagnosisbroken rotor bar demodulationwavelet transform
PACS:
TM 343
DOI:
-
Abstract:
 Abstract:Spectrum leakages make it difficult to identify fault feature during early diagnostics of squirrel cage induction motor broken rotor bars with motor current signature analysis(MCSA) method. A diagnosis
method based on Morlet wavelet demodulated current signal was proposed to overcome this problem. The fast Fourier transform(FFT) spectrum of the envelope of stator current was investigated and the conclusion of failure or not was drawn depending on the situation that characteristic frequency of 2吠could be found in obtained spectrum. The envelope extraction was performed by Morlet wavelet demodulation algorithm with proper selected wavelet parameters and used to remove the strong fundamental frequency and additional
components outside the frequency region of interest. For main-fed or inverter-fed motor operating under different load conditions,the proposed method can all eliminate noises and fundamental frequency,which make feature extraction easier for the purpose of incipient diagnosis of broken rotor bars. The theoretical analvsis andexperimental results show the effectiveness of the proposed methods.

References:

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Memo:
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Last Update: 2015-07-18