Compound Faults Feature Extraction for Rolling Bearings Based on Parallel Dual-Q-Factors and the Improved Maximum Correlated Kurtosis Deconvolution

Compound Faults Feature Extraction for Rolling Bearings Based on Parallel Dual-Q-Factors and the Improved Maximum Correlated Kurtosis Deconvolution

Vibration analysis is one of the main effective ways for rolling bearing fault diagnosis, and a challenge is how to accurately separate the inner and outer race fault features from noisy compound faults signals. Therefore, a novel compound fault separation algorithm based on parallel dual-Q-factors...

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Bibliographic Details
Main Authors: Lingli Cui, Jianxi Du, Na Yang, Yonggang Xu, Liuyang Song
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Applied Sciences
Subjects:
rolling bearings
compound faults
fault features
parallel dual-Q-factor
MCKD
Online Access:https://www.mdpi.com/2076-3417/9/8/1681

Internet

https://www.mdpi.com/2076-3417/9/8/1681

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