Milling Chatter Prediction Based on the Information Entropy and Support Vector Machine

被引：0
|
作者：
Chen Bing [1 ]
Yang Jie [1 ]
Zhao Ju [1 ]
Ren Jingbo [1 ]
机构：
[1] Northwestern Polytech Univ, Minist Educ, Key Lab Contemporary Design & Integrated Mfg Tech, Xian 710072, Shannxi, Peoples R China
来源：
PROCEEDINGS OF THE 2015 INTERNATIONAL INDUSTRIAL INFORMATICS AND COMPUTER ENGINEERING CONFERENCE | 2015年
关键词：
Milling Chatter Prediction; Multi-scale Permutation Entropy; Wavelet Packet Energy entropy; Support Vector Machine;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes a method based on information entropy and support vector machine predict chatter in milling, it uses multi-scale permutation entropy and wavelet packet energy as the milling chatter premonition features, we select parameters of these identifying features by experimental analysis, and predict chatter using the SVM which use these two identifying features as its input. The results show that this method can effectively predict the occurrence of milling chatter, correct rate is 95.8%.
引用
收藏
页码：376 / 380
页数：5
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