Fault Diagnosis of Rolling Bearing Based on an Improved Denoising Technique Using Complete Ensemble Empirical Mode Decomposition and Adaptive Thresholding Method-Reference-Cited by-同舟云学术

Fault Diagnosis of Rolling Bearing Based on an Improved Denoising Technique Using Complete Ensemble Empirical Mode Decomposition and Adaptive Thresholding Method

Published:2022-06-24 Issue:2 Volume:11 Page:513-535
ISSN:2523-3920
Container-title:Journal of Vibration Engineering & Technologies
language:en
Short-container-title:J. Vib. Eng. Technol.

Author:

Sahu Prashant Kumar^ORCID,Rai Rajiv Nandan

Publisher

Springer Science and Business Media LLC

Subject

Microbiology (medical),Immunology,Immunology and Allergy

Link

https://link.springer.com/content/pdf/10.1007/s42417-022-00591-z.pdf

Reference36 articles.

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3. Jardine AKS, Lin D, Banjevic D (2006) A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mech Syst Signal Process 20:1483–1510. https://doi.org/10.1016/j.ymssp.2005.09.012

4. Heng RBW, Nor MJM (1998) Statistical analysis of sound and vibration signals for monitoring rolling element bearing condition. Appl Acoust 53(1–3):211–226. https://doi.org/10.1016/s0003-682x(97)00018-2

5. Aasi A, Tabatabaei R, Aasi E, Jafari SM (2021) Experimental investigation on time-domain features in the diagnosis of rolling element bearings by acoustic emission. JVC J Vib Control. https://doi.org/10.1177/10775463211016130

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