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Transfer Learning Based Fault Diagnosis with Missing Data Due to Multi-Rate Sampling
Deep learning is an effective feature extraction method widely applied in fault diagnosis fields since it can extract fault features potentially involved in multi-sensor data. But different sensors equipped in the system may sample data at different sampling rates, which will inevitably result in a...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6514833/ https://www.ncbi.nlm.nih.gov/pubmed/30999589 http://dx.doi.org/10.3390/s19081826 |