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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Detalles Bibliográficos
Autores principales: Shi, Huibin, Fu, Wenlong, Li, Bailin, Shao, Kaixuan, Yang, Duanhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145724/
https://www.ncbi.nlm.nih.gov/pubmed/33923036
http://dx.doi.org/10.3390/e23050527

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145724/
https://www.ncbi.nlm.nih.gov/pubmed/33923036
http://dx.doi.org/10.3390/e23050527

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