A Convolutional Transformer Architecture for Remaining Useful Life Estimation
Author:
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9612652/9612653/09612814.pdf?arnumber=9612814
Cited by 13 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. HMDM: A hybrid GM model-based and MHSA-GRU data-driven method for remaining useful life prediction of rolling bearings;Journal of Vibration and Control;2024-08-18
2. Prediction of remaining useful life for rolling bearing based on ISOMAP and multi-head self-attention with gated recurrent unit;Journal of Vibration and Control;2024-08-05
3. A Lifetime Prediction Approach Based on Adversarial Variational Auto-Encoder Networks for Dry-Type Power Transformers;2023 IEEE International Conference on Energy Technologies for Future Grids (ETFG);2023-12-03
4. RUL Prediction Architecture of Rolling Bearing Considering Failure Behavior Determination;2023 Global Reliability and Prognostics and Health Management Conference (PHM-Hangzhou);2023-10-12
5. Retrieval of Injection Molding Industrial Knowledge Graph Based on Transformer and BERT;Applied Sciences;2023-05-31
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