Intelligent fault diagnosis of storage stacking machinery under variable working conditions using attention-based adaptive multimodal feature fusion networks
| Author(s): |
Xiangyin Meng
(School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China)
Yang Li (Institute of Smart City and Intelligent Transportation, Southwest Jiaotong University, Chengdu, China) Xinxin Xie (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China) Zhicheng Peng (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China) Shichu Li (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China) Lei Xie (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China) Huiping Huang (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China) Jian Zhang (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China) Peng Guo (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China) Min Zhang (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China) Shide Xiao (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China) |
|---|---|
| Medium: | journal article |
| Language(s): | English |
| Published in: | Structural Health Monitoring, February 2024, n. 6, v. 23 |
| Page(s): | 3465-3485 |
| DOI: | 10.1177/14759217241227163 |
- About this
data sheet - Reference-ID
10775648 - Published on:
29/04/2024 - Last updated on:
10/11/2024
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