Deep Learning Algorithms for Bearing Fault Diagnostics - A Review-Reference-Cited by-同舟云学术

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Deep Learning Algorithms for Bearing Fault Diagnostics - A Review

Published:2019-08 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE 12th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED)
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Author:

Zhang Shen,Zhang Shibo,Wang Bingnan,Habetler Thomas G.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8856151/8864799/08864915.pdf?arnumber=8864915

Cited by 58 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel bearing fault diagnosis method for compound defects via zero-shot learning;Journal of Mechanical Science and Technology;2024-09

2. A novel fault diagnosis method for imbalanced datasets based on MCNN‐Transformer model in industrial processes;International Journal of Adaptive Control and Signal Processing;2024-04-15

3. Application of deep learning to fault diagnosis of rotating machineries;Measurement Science and Technology;2024-01-25

4. A Low-Power Hierarchical CNN Hardware Accelerator for Bearing Fault Diagnosis;IEEE Transactions on Instrumentation and Measurement;2024

5. MixerFormer-Covariance Metric Neural Network: A New Few-shot Learning Model for Bearing Fault Diagnosis;2023 12th International Conference on Control, Automation and Information Sciences (ICCAIS);2023-11-27

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