Bearing Fault Diagnosis Method Based on Ensemble Composite Multi-Scale Dispersion Entropy and Density Peaks Clustering

Bearing Fault Diagnosis Method Based on Ensemble Composite Multi-Scale Dispersion Entropy and Density Peaks Clustering

For bearing fault diagnosis, how to effectively extract informative fault information and accurately diagnose faults is still a key problem. To this end, this study proposes a novel bearing fault diagnosis approach based on ensemble composite multi-scale dispersion entropy (ECMDE), local preserving...

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Bibliographic Details
Main Authors: Ai-Song Qin, Han-Ling Mao, Qin Hu, Qing-Hua Zhang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Ensemble composite multi-scale dispersion entropy
local preserving projections
density peaks clustering
noise robustness
fault diagnosis
Online Access:https://ieeexplore.ieee.org/document/9344691/

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