Automatic fault feature extraction of mechanical anomaly on induction motor bearing using ensemble super-wavelet transform-Reference-Cited by-同舟云学术

Automatic fault feature extraction of mechanical anomaly on induction motor bearing using ensemble super-wavelet transform

Published:2015-03 Issue: Volume:54-55 Page:457-480
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

He Wangpeng,Zi Yanyang,Chen Binqiang,Wu Feng,He Zhengjia

Funder

National Natural Science Foundation of China

Key Project of National Natural Science Foundation of China

Important National Science and Technology Specific Projects

National Basic Research Program of China (“973” Program)

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference46 articles.

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2. Induction motors bearing fault detection using pattern recognition techniques;Zarei;Expert Syst. Appl.,2012

3. Approximate entropy as a diagnostic tool for machine health monitoring;Yan;Mech. Syst. Sig. Process,2007

4. Weak fault feature extraction of rolling bearing based on cyclic Wiener filter and envelope spectrum;Ming;Mech. Syst. Signal Process,2011

5. Rolling element bearing diagnostics—a tutorial;Randall;Mech. Syst. Sig. Process,2011

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