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Rolling Bearing Fault Monitoring for Sparse Time-Frequency Representation and Feature Detection Strategy
Data-driven fault diagnosis methods for rotating machinery have developed rapidly with the help of deep learning methods. However, traditional intelligent fault diagnosis methods still have some limitations in fault feature extraction and the latest object detection theory has not been applied in fa...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9778231/ https://www.ncbi.nlm.nih.gov/pubmed/36554227 http://dx.doi.org/10.3390/e24121822 |