Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition

Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition

Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool con...

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Bibliographic Details
Main Author: Alessandra Caggiano
Format: Article
Language:English
Published: MDPI AG 2018-03-01
Series:Sensors
Subjects:
turning
titanium alloy
tool condition monitoring
sensor fusion
dimensionality reduction
principal component analysis
machine learning
artificial neural network
Online Access:http://www.mdpi.com/1424-8220/18/3/823

Internet

http://www.mdpi.com/1424-8220/18/3/823

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