文献类型：会议论文

英文题名：The Application of GA-BP Algorithm in Prediction of Tool Wear State

作者：Tang Jun[1];Li Wenxing[1];Zhao Bo[1,2]

第一作者：唐军

通讯作者：Tang, J[1]

机构：[1]Xinxiang Univ, Dept Mech & Elect Engn, Xinxiang 453003, Peoples R China;[2]Henan Polytech Univ, Sch Mech & Power Engn, Jiaozuo 45400, Peoples R China

第一机构：新乡学院机电工程学院

通讯机构：[1]corresponding author), Xinxiang Univ, Dept Mech & Elect Engn, Xinxiang 453003, Peoples R China.|[1107111]新乡学院机电工程学院;[11071]新乡学院;

会议论文集：5th International Conference on Mechanical, Automotive and Materials Engineering (CMAME)

会议日期：AUG 01-03, 2017

会议地点：Guangzhou, PEOPLES R CHINA

语种：英文

外文关键词：component; Genetic algorithm; BP neural network; Monitoring Current; Tool wear

摘要：In CNC shaping milling machine, the prediction of the state of tool wear has important application significance to improve productivity, reduce scrap rate and avoid security risks. In this paper, the detection and control system of disk milling cutter is set up by the current monitoring method, the input characteristic quantity and target characteristic quantity of BP neural network for tool wear diagnosis are measured, and the disk milling cutter wear condition prediction neural network is established based on the GA-BP algorithm. At last, the online prediction of milling cutter wear state is realized. The network test results show that the prediction rate of tool wear condition is more than 92.78%. So, it has certain engineering application value.