Bayesian-Optimized Hybrid Kernel SVM for Rolling Bearing Fault Diagnosis
We propose a new fault diagnosis model for rolling bearings based on a hybrid kernel support vector machine (SVM) and Bayesian optimization (BO). The model uses discrete Fourier transform (DFT) to extract fifteen features from vibration signals in the time and frequency domains of four bearing failu...
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| Autori principali: | , , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2023-05-01
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| Serie: | Sensors |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/1424-8220/23/11/5137 |
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