A novel framework based on adaptive Multi-Task learning for bearing fault diagnosis

A novel framework based on adaptive Multi-Task learning for bearing fault diagnosis

Bearing fault diagnosis is very important for the security and efficiency of electric machines. In recent years, the newly emerging deep learning methods have risen bearing fault diagnosis as a research hotspot again. To achieve better performance and interpretability and absorb novel methods, this...

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Bibliographic Details
Main Authors: Jierui Zhang, Jianjun Chen, Huiwen Deng, Weihao Hu
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:Energy Reports
Subjects:
Bearing fault diagnosis
Multi-Task Learning (MTL)
Convolutional neural network (CNN)
Gramian Angular Fields (GAF)
Markov Transition Fields (MTF)
Data augmentation (DA)
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484723006285

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http://www.sciencedirect.com/science/article/pii/S2352484723006285

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