Bearing fault diagnosis based on an improved morphological filter-Reference-Cited by-同舟云学术

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Bearing fault diagnosis based on an improved morphological filter

Published:2016-02 Issue: Volume:80 Page:163-178
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Hu Zhiyong,Wang Chao,Zhu Jun,Liu Xingchen,Kong Fanrang

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference22 articles.

1. The spectral kurtosis: a useful tool for characterising non-stationary signals;Antoni;Mech. Syst. Sig. Process.,2006

2. Fast computation of the kurtogram for the detection of transient faults;Antoni;Mech. Syst. Sig. Process.,2007

3. Short-time matrix series based singular value decomposition for rolling bearing fault diagnosis;Cong;Mech. Syst. Sig. Process.,2013

4. CWRU, Bearing Data Center, 2011 from .

5. Faults diagnosis of rolling element bearings based on modified morphological method;Dong;Mech. Syst. Sig. Process.,2011

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4. Selective weighted multi-scale morphological filter for fault feature extraction of rolling bearings;ISA Transactions;2023-01

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