A Novel Machine Learning-Based Methodology for Tool Wear Prediction Using Acoustic Emission Signals

There is an increasing trend in the industry of knowing in real-time the condition of their assets. In particular, tool wear is a critical aspect, which requires real-time monitoring to reduce costs and scrap in machining processes. Traditionally, for the purpose of predicting tool wear conditions i...

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Detalles Bibliográficos
Autores principales: Ferrando Chacón, Juan Luis, Fernández de Barrena, Telmo, García, Ander, Sáez de Buruaga, Mikel, Badiola, Xabier, Vicente, Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434684/
https://www.ncbi.nlm.nih.gov/pubmed/34502874
http://dx.doi.org/10.3390/s21175984

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434684/
https://www.ncbi.nlm.nih.gov/pubmed/34502874
http://dx.doi.org/10.3390/s21175984

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