Fault diagnosis method of bearing utilizing GLCM and MBASA-based KELM

In this study, fault diagnosis method of bearing utilizing gray level co-occurrence matrix (GLCM) and multi-beetles antennae search algorithm (MBASA)-based kernel extreme learning machine (KELM) is presented. In the proposed method, feature extraction of time–frequency image based on GLCM is propose...

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Detalles Bibliográficos
Autores principales: Fei, Sheng-wei, Liu, Ying-zhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9576792/
https://www.ncbi.nlm.nih.gov/pubmed/36253422
http://dx.doi.org/10.1038/s41598-022-19209-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9576792/
https://www.ncbi.nlm.nih.gov/pubmed/36253422
http://dx.doi.org/10.1038/s41598-022-19209-1

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