An enhanced deep intelligent model with feature fusion and ensemble learning for the fault diagnosis of rotating machinery
| Author(s): |
Kejia Zhuang
(School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China)
Bin Deng (School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China) Huai Chen (School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China) Li Jiang (School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China) Yibing Li (School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China) Jun Hu 
(School of Civil Engineering and Architecture, Wuhan University of technology, Wuhan, China)
Heungfai Lam (Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China) |
|---|---|
| Medium: | journal article |
| Language(s): | English |
| Published in: | Structural Health Monitoring |
| DOI: | 10.1177/14759217241298490 |
- About this
data sheet - Reference-ID
10812088 - Published on:
17/01/2025 - Last updated on:
17/01/2025
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