Feature Extraction Using Sparse Kernel Non-Negative Matrix Factorization for Rolling Element Bearing Diagnosis

For early fault detection of a bearing, the localized defect generally brings a complex vibration signal, so it is difficult to detect the periodic transient characteristics from the signal spectrum using conventional bearing fault diagnosis methods. Therefore, many matrix analysis technologies, suc...

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Detalles Bibliográficos
Autores principales: Liang, Lin, Ding, Xingyun, Liu, Fei, Chen, Yuanming, Wen, Haobin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8198267/
https://www.ncbi.nlm.nih.gov/pubmed/34070578
http://dx.doi.org/10.3390/s21113680

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8198267/
https://www.ncbi.nlm.nih.gov/pubmed/34070578
http://dx.doi.org/10.3390/s21113680

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