基于GA-BP和RCSA的加工空间刀尖频响预测  

Prediction of Tool Tip Frequency Response in Machining Space Based on GA-BP and RCSA

作　　者：王贤钧 王玲[1] 李洋洋 殷国富[1] WANG Xianjun;WANG Ling;LI Yangyang;YIN Guofu(School of Mechanical Engineering,Sichuan University,Chengdu 610065,China)

机构地区：[1]四川大学机械工程学院,成都610065

出　　处：《组合机床与自动化加工技术》2023年第9期39-43,47,共6页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：四川省科技成果转移转化示范项目(2020ZHCG0026)。

摘　　要：针对机床主轴加工位置变化和刀具更换引起刀尖频响函数改变的现象,提出了一种基于遗传算法优化的反向神经网络(GA-BP)和子结构响应耦合方法(RCSA)的刀尖加工空间频响函数预测方法。在该方法中,将机床系统划分为刀柄基座、剩余刀柄和刀具3个子结构。采取GA-BP算法构建刀柄基座频响函数预测模型;通过遗传算法辨识刀柄-刀具结合面参数;最后,采用RCSA法预测出不同加工位置和不同刀具的刀尖点频响函数。结果表示,刀尖点频响函数的预测值与实测值基本一致,前二阶固有频率的误差均不超过5%,有效地验证了该方法的可行性和准确性,为不同位置和不同刀具下的频响函数预测提供了有效参考。Aiming at the phenomenon that the frequency response function of tool tip changes due to the change of machining position of machine tool spindle and tool replacement,a prediction method of tool tip machining space frequency response function based on genetic algorithm optimized inverse neural network(GA-BP)and substructure response coupling method(RCSA)was proposed.In this method,the machine tool system is divided into three sub structures:tool holder base,residual tool holder and tool.GA-BP algorithm is adopted to build the prediction model of the frequency response function of the tool holder base;The parameters of tool holder tool interface are identified by genetic algorithm;Finally,the RCSA method is used to predict the tool tip frequency response functions of different machining positions and different tools.The results show that the predicted value of the tool tip frequency response function is basically consistent with the measured value,and the errors of the first and second natural frequencies are not more than 5%,which effectively verifies the feasibility and accuracy of this method,and provides an effective reference for the prediction of the frequency response function at different positions and under different tools.

关 键 词：刀尖频响函数 GA-BP RSCA 加工空间 

分 类 号：TH162[机械工程—机械制造及自动化] TG61[金属学及工艺—金属切削加工及机床]