Feature Space Transformation for Fault Diagnosis of Rotating Machinery under Different Working Conditions

In recent years, various deep learning models have been developed for the fault diagnosis of rotating machines. However, in practical applications related to fault diagnosis, it is difficult to immediately implement a trained model because the distribution of source data and target domain data have...

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Detalles Bibliográficos
Autores principales: Jang, Gye-Bong, Cho, Sung-Bae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7922640/
https://www.ncbi.nlm.nih.gov/pubmed/33670547
http://dx.doi.org/10.3390/s21041417

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7922640/
https://www.ncbi.nlm.nih.gov/pubmed/33670547
http://dx.doi.org/10.3390/s21041417

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