Adaptive network fuzzy inference system and support vector machine learning for tool wear estimation in high speed milling processes

• Main Authors: Ge, H., Huang, S., Torabi, Amin J., Li, X., Er, Meng Joo, Gan, Oon Peen, Zhai, Lian yin, San, Linn
• 其他作者: School of Electrical and Electronic Engineering
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2013
• 主題: DRNTU::Engineering::Electrical and electronic engineering
• 在線閱讀: https://hdl.handle.net/10356/101096; http://hdl.handle.net/10220/16312

In metal cutting processes, tool condition monitoring (TCM) plays an important role in maintaining the quality of surface finishing. Monitoring of tool wear in order to prevent surface damage is one of the difficult tasks in the context of TCM. Through early detection, high quality surface finishing...