Complex Working Condition Bearing Fault Diagnosis Based on Multi-Feature Fusion and Improved Weighted Balance Distribution Adaptive Approach

Complex Working Condition Bearing Fault Diagnosis Based on Multi-Feature Fusion and Improved Weighted Balance Distribution Adaptive Approach

In order to improve the accuracy and generalization ability of fault diagnosis for rotating machinery bearings under complex working conditions, a new model based on multi-feature fusion and improved weighted balance distribution adaptation is proposed. Firstly, an optimized variational mode decompo...

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Bibliographic Details
Main Authors: Jing Yang, Yanping Bai, Ting Xu, Rong Cheng, Wendong Zhang, Guojun Zhang
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Lubricants
Subjects:
fault diagnosis
feature extraction
multi-feature fusion
transfer learning
variable working conditions
Online Access:https://www.mdpi.com/2075-4442/13/5/221
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