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...

Descripción completa

Detalles Bibliográficos
Autores principales: Song, Xinmin, Wei, Weihua, Zhou, Junbo, Ji, Guojun, Hussain, Ghulam, Xiao, Maohua, Geng, Guosheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255357/
https://www.ncbi.nlm.nih.gov/pubmed/37299863
http://dx.doi.org/10.3390/s23115137

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255357/
https://www.ncbi.nlm.nih.gov/pubmed/37299863
http://dx.doi.org/10.3390/s23115137

Ejemplares similares