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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Главные авторы:	Xinmin Song, Weihua Wei, Junbo Zhou, Guojun Ji, Ghulam Hussain, Maohua Xiao, Guosheng Geng
Формат:	Artigo
Язык:	Inglês
Опубликовано:	MDPI AG 2023-05-01
Серии:	Sensors
Предметы:	Bayesian optimization rolling bearing fault diagnosis hybrid kernel SVM
Online-ссылка:	https://www.mdpi.com/1424-8220/23/11/5137
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