A multi fault classification in a rotor-bearing system using machine learning approach-Reference-Cited by-同舟云学术

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A multi fault classification in a rotor-bearing system using machine learning approach

Published:2023-02 Issue:2 Volume:45 Page:
ISSN:1678-5878
Container-title:Journal of the Brazilian Society of Mechanical Sciences and Engineering
language:en
Short-container-title:J Braz. Soc. Mech. Sci. Eng.

Author:

Shinde Prasad V.,Desavale R. G.,Jadhav P. M.,Sawant Sanjay H.

Publisher

Springer Science and Business Media LLC

Subject

Mechanical Engineering,General Engineering,Aerospace Engineering,Automotive Engineering,Industrial and Manufacturing Engineering,Applied Mathematics

Link

https://link.springer.com/content/pdf/10.1007/s40430-023-04015-1.pdf

Reference26 articles.

1. Fan Y, Zhang C, Xue Y, Wang J, Gu F (2020) A bearing fault diagnosis using a support vector machine optimised by the self-regulating particle swarm. Shock Vib. https://doi.org/10.1155/2020/9096852

2. Kedadouche M, Liu Z (2017) Fault feature extraction and classification based on WPT and SVD: application to element bearings with artificially created faults under variable conditions. Proc Ins Mech Eng Part C J Mech Eng Sci 231(22):4186–4196. https://doi.org/10.1177/0954406216663782

3. Guo L, Chen J, Li X (2009) Rolling bearing fault classification based on envelope spectrum and support vector machine. JVC Journal Vib Control 15(9):1349–1363. https://doi.org/10.1177/1077546308095224

4. Xu F, Wai Tat TSE P, Fang YJ, Liang JQ (2019) A fault diagnosis method combined with compound multiscale permutation entropy and particle swarm optimization–support vector machine for roller bearings diagnosis. Proc Inst Mech Eng Part J J Eng Tribol 233(4):615–627. https://doi.org/10.1177/1350650118788929

5. Lin CJ, Chu WL, Wang CC, Chen CK, Chen IT (2020) Diagnosis of ball-bearing faults using support vector machine based on the artificial fish-swarm algorithm. J Low Freq Noise Vib Act Control 39(4):954–967. https://doi.org/10.1177/1461348419861822

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1. A Novel Method for Bearing Fault Diagnosis Based on Novel Feature Sets With Machine Learning Technique;Journal of Tribology;2024-09-13

2. Identification and Fault Diagnosis of Rolling Element Bearings Using Dimension Theory and Machine Learning Techniques;Journal of Tribology;2024-05-15

3. An investigation of dynamic characteristics in rotor-bearing system with combined bearing and coupling defects;Journal of the Brazilian Society of Mechanical Sciences and Engineering;2024-05-06

4. Fault diagnosis of rotating machinery using novel self-attention mechanism TCN with soft thresholding method;Measurement Science and Technology;2024-01-31

5. A Dynamic Model of Outer Race Defective Bearing Considering the Unbalanced Shaft-Bearing System With Experimental Simulation;Journal of Tribology;2023-10-05

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