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A Bearing Fault Diagnosis Model based on Minimum Average Composite Entropy and Parallel Attention Mechanism Convolutional Neural Network Cover

A Bearing Fault Diagnosis Model based on Minimum Average Composite Entropy and Parallel Attention Mechanism Convolutional Neural Network

Measurement Science Review
Volume 25 (2025): Issue 4 (August 2025)
By: Zhen Zhang,  Shixi Yang,  Jun He,  Wanchun Zhou and  Yanxu Liu  
Open Access
|Aug 2025

Authors

Zhen Zhang

zhangzhen1986217@163.com

Henan University of Technology, Zhengzhou, China
Zhejiang University - Zhongyuan Institute, Zhengzhou, China

Shixi Yang

School of Mechanical Engineering, Zhejiang University, Hangzhou, China
Zhejiang University - Zhongyuan Institute, Zhengzhou, China

Jun He

School of Mechanical Engineering, Zhejiang University, Hangzhou, China
Zhejiang University - Zhongyuan Institute, Zhengzhou, China

Wanchun Zhou

Zhejiang University - Zhongyuan Institute, Zhengzhou, China

Yanxu Liu

Zhejiang University - Zhongyuan Institute, Zhengzhou, China
DOI: https://doi.org/10.2478/msr-2025-0022 | Journal eISSN: 1335-8871
Journal RSS Feed
Language: English
Page range: 178 - 189
Submitted on: Feb 28, 2025
|
Accepted on: May 27, 2025
|
Published on: Aug 14, 2025
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
Renyi entropy,
fusion attention mechanism,
parallel convolutional neural network,
rolling bearings,
Gramian angle field
Related subjects:
Engineering,
Electrical engineering,
Control engineering, metrology and testing

© 2025 Zhen Zhang, Shixi Yang, Jun He, Wanchun Zhou, Yanxu Liu, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.

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