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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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2021-09, Vol.21 (17), p.5984
Main Authors: Ferrando Chacón, Juan Luis, Fernández de Barrena, Telmo, García, Ander, Sáez de Buruaga, Mikel, Badiola, Xabier, Vicente, Javier
Format: Article
Language:English
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