Intelligent Fault Diagnosis of Rolling Bearing Using FCM Clustering of EMD-PWVD Vibration Images

Intelligent Fault Diagnosis of Rolling Bearing Using FCM Clustering of EMD-PWVD Vibration Images

Rolling bearing is key component of rotating machinery and its fault diagnosis is of great significance for reliable operation of machine. In this paper, an intelligent fault diagnosis method of rolling bearing based on FCM clustering of vibration images obtained by EMD-PWVD is presented. Firstly, v...

Full description

Bibliographic Details
Main Authors: Hongwei Fan, Sijie Shao, Xuhui Zhang, Xiang Wan, Xiangang Cao, Hongwei Ma
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Rolling bearing
fault diagnosis
vibration image
empirical mode decomposition (EMD)
pesudo-Wigner-Ville distribution (PWVD)
fuzzy C-means (FCM) clustering
Online Access:https://ieeexplore.ieee.org/document/9151133/

Internet

https://ieeexplore.ieee.org/document/9151133/

Similar Items