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View all- Sun YJin Z(2023)Research on fault diagnosis method of bearing based on parameter optimization VMD and improved DBNJournal of Vibroengineering10.21595/jve.2023.22770Online publication date: 8-Sep-2023
VMD Entropy Method and Its Application in Early Fault Diagnosis of Bearing
Authors: 
Hang Jin, Jianhui Lin, Xieqi ChenAuthors Info & Claims
Hang Jin, Jianhui Lin, Xieqi ChenAuthors Info & ClaimsAbstract
This paper proposes an early faults diagnosis method for bearings based on Variational Mode Decomposition (VMD) and Entropy Theory to monitor the working state of the key components of the high-speed train axle box. Firstly, the box vibration signal is decomposed into detailed signals at different scales by using VMD (Band-Limited Intrinsic Mode Function, BIMF), then the three kinds of entropy are extracted from BIMF and composed into VMD entropy. Finally, the VMD entropy has been input into SVM for training to determine the fault type. This paper is going to take research on the vibration signals of high-speed train axle box under three typical working conditions of normal bearing, cage failure and roller failure. It is concluded that the best VMD parameters of fault identification for high-speed train axle box can effectively improve the recognition rate of entropy in early bearing fault diagnosis by comparing it with EMD entropy. The analysis results show that for a high-speed train running under 200 km/h, the recognition rates under three different working conditions can reach 98.75%, 100%, 98.75% respectively, which proved the validity of VMD entropy for early bearing fault identification of high-speed train.
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- VMD Entropy Method and Its Application in Early Fault Diagnosis of Bearing
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Published In
November 2018
177 pages
ISBN:9781450366052
DOI:10.1145/3297067
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Association for Computing Machinery
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Published: 28 November 2018
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- the Sichuan Natural Science Foundation
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SPML '18
SPML '18: 2018 International Conference on Signal Processing and Machine Learning
November 28 - 30, 2018
Shanghai, China
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View all- Sun YJin Z(2023)Research on fault diagnosis method of bearing based on parameter optimization VMD and improved DBNJournal of Vibroengineering10.21595/jve.2023.22770Online publication date: 8-Sep-2023
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