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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...
Autores principales: | Maliuk, Andrei S., Prosvirin, Alexander E., Ahmad, Zahoor, Kim, Cheol Hong, Kim, Jong-Myon |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
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 |
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