现代制造工程Issue(12)：68-72,5.
基于小波包和 BP 神经网络的刀具磨损状态识别
Recognition of tool wear state based on wavelet packet and BP neural network
摘要
Abstract
The state of tool wear influences the metal cutting process ,so the monitoring of cutting tool wear condition is an impor-tance for improving the quality of the products .The tool wear condition monitoring system is designed .The tool vibration signals are collected with sensors and analyzed by wavelet packet .The feature value of tool wear state is extracted from the different fre-quency band energy .Using the BP neural network ,the mapping relationship between the tool wear and vibration signal feature is established.Therefore,the tool wear condition monitoring is completed .The system is realized using C ++Builder and Matlab mixed programming .The experiments show that the system identifies the tool wear state correctly .关键词
刀具磨损/监测/小波包/神经网络Key words
tool wear/monitoring/wavelet packet/neural network分类
信息技术与安全科学引用本文复制引用
库祥臣,周芸梦,高鹏磊,段明德..基于小波包和 BP 神经网络的刀具磨损状态识别[J].现代制造工程,2014,(12):68-72,5.基金项目
国家科技重大专题项目 （）
