Morphological Filtering Algorithm for Estimation of Tool Wear in CNC Milling Machining

被引：1

作者：

Ning, Q. ^{[1
]}

Wang, T. Y. ^{[1
]}

机构：

[1] Tianjin Univ, Sch Mech Engn, Tianjin 300072, Peoples R China

来源：

ADVANCES IN MATERIALS MANUFACTURING SCIENCE AND TECHNOLOGY XIV | 2012年 / 697-698卷

关键词：

Morphological filter; Tool wear; Support vector machine; Pattern recognition; NEURAL-NETWORK; FUSION;

D O I：

10.4028/www.scientific.net/MSF.697-698.566

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Estimation of tool condition has very important meaning to improve the product quality, continuous machining ability and reliability of the manufacturing system. Based on mathematical morphology, a systematic approach is developed to implement online estimation of tool wear in this paper. As the nonlinear filter, morphological filter is selected to reduce the higher frequency noises before feature values extraction. The feature vector consists of original characteristics of vibration signal and cutting force signal. Then, they are input into SVM for training and testing. Experiments show that this method can achieve tool wear estimation effectively.

引用

页码：566 / 569

页数：4

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