Transfer-Learning-Based Estimation of the Remaining Useful Life of Heterogeneous Bearing Types Using Low-Frequency Accelerometers

Deep learning approaches are becoming increasingly important for the estimation of the Remaining Useful Life (RUL) of mechanical elements such as bearings. This paper proposes and evaluates a novel transfer learning-based approach for RUL estimations of different bearing types with small datasets an...

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Detalles Bibliográficos
Autores principales: Schwendemann, Sebastian, Sikora, Axel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9962409/
https://www.ncbi.nlm.nih.gov/pubmed/36826953
http://dx.doi.org/10.3390/jimaging9020034

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9962409/
https://www.ncbi.nlm.nih.gov/pubmed/36826953
http://dx.doi.org/10.3390/jimaging9020034

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