Fault diagnosis method based on integration of RSSD and wavelet transform to rolling bearing

Author:

Chen Baojia,Shen Baoming,Chen Fafa,Tian Hongliang,Xiao Wenrong,Zhang Fajun,Zhao Chunhua

Funder

National Nature Science Foundation of China

Natural Science Foundation of Hubei Province of China

Hubei Key Laboratory of Hydroelectric Machinery Design & Maintenance

Publisher

Elsevier BV

Subject

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

Reference25 articles.

1. Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery;Lei,2016

2. Rolling element bearing fault diagnosis using wavelet transform;Kankar;Neurocomputing,2011

3. Multiwavelet denoising with improved neighboring coefficients for application on rolling bearing fault diagnosis;Wang;Mech. Syst. Signal Process.,2011

4. A review on empirical mode decomposition in fault diagnosis of rotating machinery;Lei;Mech. Syst. Signal Process.,2013

5. Wavelet-based approach for online fuel cell remaining useful lifetime prediction;Ibrahim;IEEE Trans. Ind. Electron.,2016

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