Novel Bearing Fault Diagnosis Using Gaussian Mixture Model-Based Fault Band Selection

This paper proposes a Gaussian mixture model-based (GMM) bearing fault band selection (GMM-WBBS) method for signal processing. The proposed method benefits reliable feature extraction using fault frequency oriented Gaussian mixture model (GMM) window series. Selecting exclusively bearing fault frequ...

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Detalles Bibliográficos
Autores principales: Maliuk, Andrei S., Prosvirin, Alexander E., Ahmad, Zahoor, Kim, Cheol Hong, Kim, Jong-Myon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512720/
https://www.ncbi.nlm.nih.gov/pubmed/34640899
http://dx.doi.org/10.3390/s21196579

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512720/
https://www.ncbi.nlm.nih.gov/pubmed/34640899
http://dx.doi.org/10.3390/s21196579

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