Feature Extraction Method of Rolling Bearing Fault Signal Based on EEMD and Cloud Model Characteristic Entropy

Feature Extraction Method of Rolling Bearing Fault Signal Based on EEMD and Cloud Model Characteristic Entropy

The randomness and fuzziness that exist in rolling bearings when faults occur result in uncertainty in acquisition signals and reduce the accuracy of signal feature extraction. To solve this problem, this study proposes a new method in which cloud model characteristic entropy (CMCE) is set as the si...

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Bibliographic Details
Main Authors: Long Han, Chengwei Li, Hongchen Liu
Format: Article
Language:English
Published: MDPI AG 2015-09-01
Series:Entropy
Subjects:
rolling bearing
feature extraction
EEMD
cloud model characteristic entropy
Online Access:http://www.mdpi.com/1099-4300/17/10/6683

Internet

http://www.mdpi.com/1099-4300/17/10/6683

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