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

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

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...

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書目詳細資料
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
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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