FMRGAN: Feature Mapping Reconstruction GAN for Rolling Bearings Fault Diagnosis Under Limited Data Condition
Author:
Affiliation:
1. School of Measurement and Communication Engineering, Harbin University of Science and Technology, Harbin, China
2. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China
Funder
Natural Science Foundation of Heilongjiang Province
University Nursing Program for Young Scholar With Creative Talents in Heilongjiang Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/7361/10617804/10570175.pdf?arnumber=10570175
Reference43 articles.
1. Faster Multiscale Dictionary Learning Method With Adaptive Parameter Estimation for Fault Diagnosis of Traction Motor Bearings
2. A novel approach to fault diagnostics and prognostics
3. A novel method based on meta-learning for bearing fault diagnosis with small sample learning under different working conditions
4. Rolling bearing fault diagnosis based on 2D time-frequency images and data augmentation technique
5. Ventilation diagnosis of minigrinders using thermal images
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