Improved VMD‐KFCM algorithm for the fault diagnosis of rolling bearing vibration signals

Improved VMD‐KFCM algorithm for the fault diagnosis of rolling bearing vibration signals

Abstract In order to make accurate judgements of rolling bearing main fault types using the small sample size fault data set, a novel approach is put forward that combines particle swarm optimisation kernel fuzzy C‐means (PSO‐KFCM) and variational mode decomposition (VMD). Firstly, by calculating th...

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Bibliographic Details
Main Authors: Yong Chang, Guangqing Bao, Sikai Cheng, Ting He, Qiaoling Yang
Format: Article
Language:English
Published: Hindawi-IET 2021-06-01
Series:IET Signal Processing
Subjects:
fault diagnosis
fuzzy set theory
particle swarm optimisation
pattern clustering
rolling bearings
signal classification
Online Access:https://doi.org/10.1049/sil2.12026

Internet

https://doi.org/10.1049/sil2.12026

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