Application of Continuous Wavelet Features and Multi-Class Sphere SVM to Chatter Prediction

摘要：

A cutting chatter forecast method based on continuous wavelet feature and multi-class spherical Support Vector Machines is studied in this paper. The method based on continuous wavelet transform extracts the cutting vibration signal feature and uses multi-class spherical Support Vector Machines to discern the chatter. In order to simplify computational complexity when binary classification SVM turn to multi-class classification, the algorithm makes every kind of samples have a spherical SVM. In the feature space identified the test sample and spherical SVM centre distance as a decision-making function. Experiments show that using combine spherical SVM with continuous wavelet feature Vector has good recognition effect in the milling chatter recognition system. Chatter inoculation forecast accuracy reaches 95％, and chatter outbreak forecast accuracy reaches 97.5％.

关键词： Continuous wavelet Spherical SVM Multi-class SVM Chatter prediction

作者: Wu Shi D.K. Jia X.L. Liu F.G. Yan Y.F. Li

作者单位: The Key Lab of Advanced Manufacturing Tech. & Cutting Tools, Harbin Univ. of Sci. and Tech,Harbin, 1 The Key Lab of Advanced Manufacturing Tech. & Cutting Tools, Harbin Univ. of Sci. and Tech, Harbin,

会议类型: 国际会议

会议名称: The 4th International Conference on High Speed Machining(第四届高速加工国际会议 ICHSM2010)

会议地点: 武汉

会议语种:英文

页码: 675-680

在线出版日期: 2011-05-28（万方平台首次上网日期，不代表论文的发表时间）