Fault Diagnosis of Rotating Machinery Using Kernel Neighborhood Preserving Embedding and a Modified Sparse Bayesian Classification Model

Fault diagnosis of rotating machinery plays an important role in modern industrial machines. In this paper, a modified sparse Bayesian classification model (i.e., Standard_SBC) is utilized to construct the fault diagnosis system of rotating machinery. The features are extracted and adopted as the in...

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Detalles Bibliográficos
Autores principales: Lu, Lixin, Wang, Weihao, Kong, Dongdong, Zhu, Junjiang, Chen, Dongxing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10670152/
https://www.ncbi.nlm.nih.gov/pubmed/37998242
http://dx.doi.org/10.3390/e25111549

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10670152/
https://www.ncbi.nlm.nih.gov/pubmed/37998242
http://dx.doi.org/10.3390/e25111549

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