Deep learning for fault diagnosis based on multi-sourced heterogeneous data-Reference-Cited by-同舟云学术

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Deep learning for fault diagnosis based on multi-sourced heterogeneous data

Published:2014-10 Issue: Volume: Page:
ISSN:
Container-title:2014 International Conference on Power System Technology
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Author:

Yan Ma ,Zhihong Guo ,Jianjun Su ,Yufeng Chen ,Xiuming Du ,Yi Yang ,Chengqi Li ,Ying Lin ,Yujie Geng

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/6975316/6993479/06993854.pdf?arnumber=6993854

Cited by 5 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. Prognostics and Health Management of Unmanned Surface Vessels: Past, Present, and Future;Journal of Computing and Information Science in Engineering;2024-06-03

2. Power transformer fault identification based on improved BERT-wwm-ext-CNN;2023 IEEE International Conference on Sensors, Electronics and Computer Engineering (ICSECE);2023-08-18

3. Multimodal Machine Learning in Prognostics and Health Management of Manufacturing Systems;Springer Series in Reliability Engineering;2023

4. Unsupervised Joint Subdomain Adaptation Network for Fault Diagnosis;IEEE Sensors Journal;2022-05-01

5. A Comprehensive Survey of Prognostics and Health Management Based on Deep Learning for Autonomous Ships;IEEE Transactions on Reliability;2019-06

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