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The Design for High Dynamic GPS Receiver in a Combinated Method of FLL and PLL Read chapter Read first chapter

2013 | OriginalPaper | Chapter

65. The Feature Extraction of Rolling Bearing Fault Based on Wavelet Packet—Empirical Mode Decomposition and Kurtosis Rule

Authors : Cheng Wen, Chuande Zhou

Published in: Emerging Technologies for Information Systems, Computing, and Management

Publisher: Springer New York

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Abstract

The feature extraction method of rolling bearing fault was presented based on the combination of wavelet packet-EMD (empirical mode decomposition) and kurtosis rule. Its first step is to reduce the signal noise by the wavelet packet, and then do EMD decomposition. Based on the characteristic that the kurtosis is very sensitive to impact the biggest IMF component of kurtosis is selected to do Hilbert envelope demodulation. As a result, the fault feature information of rolling bearing was obtained. The implementation process of this method was analyzed by simulation signal and the method was successfully applied in inner race of rolling bearing fault diagnosis.

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Metadata
Title
The Feature Extraction of Rolling Bearing Fault Based on Wavelet Packet—Empirical Mode Decomposition and Kurtosis Rule
Authors
Cheng Wen
Chuande Zhou
Copyright Year
2013
Publisher
Springer New York
Book
Emerging Technologies for Information Systems, Computing, and Management

Print ISBN: 978-1-4614-7009-0

Electronic ISBN: 978-1-4614-7010-6

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-1-4614-7010-6_65