Intelligent Fault Identification for Rolling Bearings Fusing Average Refined Composite Multiscale Dispersion Entropy-Assisted Feature Extraction and SVM with Multi-Strategy Enhanced Swarm Optimization

Intelligent Fault Identification for Rolling Bearings Fusing Average Refined Composite Multiscale Dispersion Entropy-Assisted Feature Extraction and SVM with Multi-Strategy Enhanced Swarm Optimization

Rolling bearings act as key parts in many items of mechanical equipment and any abnormality will affect the normal operation of the entire apparatus. To diagnose the faults of rolling bearings effectively, a novel fault identification method is proposed by merging variational mode decomposition (VMD...

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Bibliographic Details
Main Authors: Huibin Shi, Wenlong Fu, Bailin Li, Kaixuan Shao, Duanhao Yang
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Entropy
Subjects:
fault identification
variational mode decomposition
average refined composite multiscale dispersion entropy
multistrategy enhanced swarm optimization algorithm
support vector machine
Online Access:https://www.mdpi.com/1099-4300/23/5/527

Internet

https://www.mdpi.com/1099-4300/23/5/527

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