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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...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| 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 |