Research on unsupervised domain adaptive bearing fault diagnosis method
Aiming at the problem that the bearing fault diagnosis algorithm based on deep learning has poor diagnosis performance when the fault samples are lack of labels in different working conditions and real environmentsly, an unsupervised domain adaptive bearing fault diagnosis method was proposed to rea...
Saved in:
Main Authors: | WU ShengKai, SHAO Xing, WANG CuiXiang, GAO Jun |
---|---|
Format: | Article |
Language: | zho |
Published: |
Editorial Office of Journal of Mechanical Strength
2024-06-01
|
Series: | Jixie qiangdu |
Subjects: | |
Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2024.03.003 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Normalization-Guided and Gradient-Weighted Unsupervised Domain Adaptation Network for Transfer Diagnosis of Rolling Bearing Faults Under Class Imbalance
by: Hao Luo, et al.
Published: (2025-01-01) -
A Target Domain-Specific Classifier Weight Partial Transfer Adversarial Network for Bearing Fault Diagnosis
by: Yin Bai, et al.
Published: (2025-01-01) -
Multi-View Prototypical Transport for Unsupervised Domain Adaptation
by: Sunhyeok Lee, et al.
Published: (2025-01-01) -
Towards a Standard Benchmarking Framework for Domain Adaptation in Intelligent Fault Diagnosis
by: Mohammed M. Farag
Published: (2025-01-01) -
Structure preserved ordinal unsupervised domain adaptation
by: Qing Tian, et al.
Published: (2024-11-01)