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A Hybrid Matching Network for Fault Diagnosis under Different Working Conditions with Limited Data
Intelligent fault diagnosis methods based on deep learning have achieved much progress in recent years. However, there are two major factors causing serious degradation of the performance of these algorithms in real industrial applications, i.e., limited labeled training data and complex working con...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270151/ https://www.ncbi.nlm.nih.gov/pubmed/35814590 http://dx.doi.org/10.1155/2022/3024590 |