Enhancing fault diagnosis with a hybrid attention mechanism and spatio-temporal feature mining model using small sample data
| Author(s): |
Zhicheng He
(State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, P. R. China)
Gang Tan (State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, P. R. China) Enlin Zhou (State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, P. R. China) Eric Li 
(School of Computing, Engineering, and Digital Technologies, Teesside University, Middlesbrough, UK)
Bian Hu (School of Energy Science and Engineering, Central South University, Changsha, P. R. China) Chongshi Li (Wuling Power Co., Ltd., Changsha, P. R. China) Bing Li (School of Aeronautics, Northwestern Polytechnical University, Xi’an, Shaanxi, China) |
|---|---|
| Medium: | journal article |
| Language(s): | English |
| Published in: | Structural Health Monitoring |
| DOI: | 10.1177/14759217241290537 |
- About this
data sheet - Reference-ID
10812138 - Published on:
17/01/2025 - Last updated on:
17/01/2025
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