A Fault Diagnosis Method of Rolling Bearing Based on Attention Entropy and Adaptive Deep Kernel Extreme Learning Machine

A Fault Diagnosis Method of Rolling Bearing Based on Attention Entropy and Adaptive Deep Kernel Extreme Learning Machine

To address the difficulty of early fault diagnosis of rolling bearings, this paper proposes a rolling bearing diagnosis method by combining the attention entropy and adaptive deep kernel extreme learning machine (ADKELM). Firstly, the wavelet threshold denoising method is employed to eliminate the n...

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Bibliographic Details
Main Authors: Weiyu Wang, Xunxin Zhao, Lijun Luo, Pei Zhang, Fan Mo, Fei Chen, Diyi Chen, Fengjiao Wu, Bin Wang
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Energies
Subjects:
rolling bearing
fault diagnosis
empirical wavelet transform
attention entropy
marine predators algorithm
deep kernel extreme learning machine
Online Access:https://www.mdpi.com/1996-1073/15/22/8423

Internet

https://www.mdpi.com/1996-1073/15/22/8423

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