Performance Prediction of Rolling Bearing Using EEMD and WCDPSO-KELM Methods
Research on bearings performance degradation trend is significant, and can greatly reduce the loss caused by potential faults in the whole life-cycle of rolling bearings. It is also a very important part of Prognostic and Health Management (PHM). This paper proposed a new performance degradation pre...
Main Authors: | Xiumei Li, Huimin Zhao |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-05-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/12/9/4676 |
Similar Items
-
Rotate Vector Reducer Fault Diagnosis Model Based on EEMD-MPA-KELM
by: Zhijian Tu, et al.
Published: (2023-03-01) -
A Novel Fault Diagnosis Method Based on the KELM Optimized by Whale Optimization Algorithm
by: Ruijun Liang, et al.
Published: (2022-01-01) -
The potential of ensemble WT-EEMD-kernel extreme learning machine techniques for prediction suspended sediment concentration in successive points of a river
by: Kiyoumars Roushangar, et al.
Published: (2021-05-01) -
Fault Diagnosis of Wind Turbine Bearings Based on CEEMDAN-GWO-KELM
by: Liping Liu, et al.
Published: (2022-12-01) -
THE EEMD-RA-KU METHOD ON DIAGNOSIS OF BEARING FAULT
by: WU GuangHe, et al.
Published: (2016-01-01)