In-process Tool Wear Prediction System Based on Machine Learning Techniques and Force Analysis-Reference-Cited by-同舟云学术

In-process Tool Wear Prediction System Based on Machine Learning Techniques and Force Analysis

Published:2018 Issue: Volume:77 Page:501-504
ISSN:2212-8271
Container-title:Procedia CIRP
language:en
Short-container-title:Procedia CIRP

Author:

Gouarir A.,Martínez-Arellano G.,Terrazas G.,Benardos P.,Ratchev S.

Publisher

Elsevier BV

Subject

General Medicine

Reference23 articles.

1. In-Process Tool Wear Detection of Uncoated Square End Mill Based on Electrical Contact Resistance;Gouarir;International Journal of Automation Technology,2016

2. Force-based model for tool wear monitoring in face milling;Lin;International Journal of Machine Tools and Manufacture,1995

3. Use of cutting force and acoustic emission signals for the monitoring of tool insert geometry during rough face milling;Wilcox;International Journal of Machine Tools and Manufacture,1997

4. Chen, J., 2003. Development of in-process tool wear prediction systems in end milling operations with dynamometer. Dissertation, Iowa State University.

5. Tool wear monitoring in face milling using force signals;Lin;Wear,1996

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