HUST bearing: a practical dataset for ball bearing fault diagnosis
Abstract Objectives The rapid growth of machine learning methods has led to an increase in the demand for data. For bearing fault diagnosis, the data acquisition is time-consuming with complicated processes. Existing datasets are only focused on only one type of bearing, which limits real-world appl...
Gorde:
| Egile Nagusiak: | , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
BMC
2023-07-01
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| Saila: | BMC Research Notes |
| Gaiak: | |
| Sarrera elektronikoa: | https://doi.org/10.1186/s13104-023-06400-4 |
| Etiketak: |
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