A novel signal denoising method using stationary wavelet transform and particle swarm optimization with application to rolling element bearing fault diagnosis-Reference-Cited by-同舟云学术

A novel signal denoising method using stationary wavelet transform and particle swarm optimization with application to rolling element bearing fault diagnosis

Published:2022 Issue: Volume:66 Page:3935-3943
ISSN:2214-7853
Container-title:Materials Today: Proceedings
language:en
Short-container-title:Materials Today: Proceedings

Author:

Laha Swarup Kumar,Swarnakar Biplab,Kansabanik Sourav,Ray Sayantani

Publisher

Elsevier BV

Subject

General Medicine

Reference23 articles.

1. Multiple band-pass autoregressive demodulation for rolling-element bearing fault diagnosis;Altmann;Mech. Syst. Sig. Process.,2001

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

3. The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines;Antoni;Mech. Syst. Sig. Process.,2006

4. Artificial neural network based fault diagnostics of rolling element bearings using time-domain features;Samanta;Mech. Syst. Sig. Process.,2003

5. Bearing fault diagnosis using FFT of intrinsic mode functions in Hilbert-Huang transform;Rai;Mech. Syst. Sig. Process.,2007

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