Real-Time Remaining Useful Life Prediction of Cutting Tools Using Sparse Augmented Lagrangian Analysis and Gaussian Process Regression

Remaining useful life (RUL) of cutting tools is concerned with cutting tool operational status prediction and damage prognosis. Most RUL prediction methods utilized different features collected from different sensors to predict the life of the tool. To increase the prediction accuracy, it is often n...

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Detalles Bibliográficos
Autores principales: Qin, Xiao, Huang, Weizhi, Wang, Xuefei, Tang, Zezhi, Liu, Zepeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824545/
https://www.ncbi.nlm.nih.gov/pubmed/36617013
http://dx.doi.org/10.3390/s23010413

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824545/
https://www.ncbi.nlm.nih.gov/pubmed/36617013
http://dx.doi.org/10.3390/s23010413

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