Engine Misfire Fault Detection Based on the Channel Attention Convolutional Model
To accurately diagnose misfire faults in automotive engines, we propose a Channel Attention Convolutional Model, specifically the Squeeze-and-Excitation Networks (SENET), for classifying engine vibration signals and precisely... | Find, read and cite all the research you need on Tech Science Press
Authors
- Feifei Yu (ORCID: https://orcid.org/0000-0003-1169-5699)
- Guoyan Chen (ORCID: https://orcid.org/0000-0001-8122-330X)
- Yongkang Gong (ORCID: https://orcid.org/0000-0003-3216-2998)
- Yongxian Huang (ORCID: https://orcid.org/0000-0003-0682-5321)
- Xiaoqing Yang (ORCID: https://orcid.org/0009-0008-4179-4720)
- Canyi Du (ORCID: https://orcid.org/0000-0002-8458-8678)
Publication Details
- Journal
- Computers, materials & continua/Computers, materials & continua (Print)
- Published
- 2024-11-21
- DOI
- https://doi.org/10.32604/cmc.2024.058051
- Citations
- 1
- Primary Topic
- Advanced Decision-Making Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.78
Funders
- Guangzhou Municipal Science and Technology Project