Research On Thermal Error Modeling And Compensation Method Of Biaxial Rotary Milling Head

As an important equipment for processing complex surfaces,five-axis machine tools are widely used in marine exploration,military defense,aviation industry,automobile transportation and other fields.Among them,as one of the most important machining parts in five-axis CNC machine tool,biaxial rotary milling head can assist CNC machine tool to achieve high-precision machining.The biaxial rotary milling head has a relatively compact internal structure,which can maintain stable machining even during high-speed machining.However,the swing head generates a large amount of heat during high speed operation,it can not dissipate heat quickly,resulting in heat accumulation and thermal error,and then reducing the processing quality.In order to solve these problems,this paper adopts a new thermal error modeling method to predict the thermal displacement of the swing head,and uses the shaft offset compensation method to send the error value into the numerical control system to realize error compensation.Firstly,the internal structure of the swing head is analyzed,and then the heating rate and heat transfer coefficient of each part of the swing head are calculated by combining the heat transfer theory and the heat generation theory.Based on this,the steady temperature field of the swing head is simulated and the steady finite element analysis of the swing head is obtained.The simulation results of the temperature field distribution obtained by analysis provide a strong theoretical basis for the design of the subsequent test scheme.Secondly,according to the simulation analysis results of the swing head,the acquisition platform of test temperature rise data and thermal displacement data was built by using related sensors and supporting detection software.The test scheme of the biaxial rotary milling head was designed according to the actual working situation,and the swing head test data of three groups under different rotating speeds were collected through the temperature rise data acquisition system and the thermal displacement data acquisition system.Then,based on the data collected from the experiment,the temperature rise data was defined as the training set,and the thermal displacement data was defined as the feature set.The support vector regression(SVR)was improved by the improved particle swarm optimization(SA-PSO)based on simulated annealing algorithm,and the thermal displacement prediction model of swing head was established.The SA-PSO-SVR model is compared with the general SVR model.The results show that the SA-PSO-SVR model has higher fitting degree,better performance and smaller prediction error.Finally,the shaft offset compensation method is used to input the compensation amount to the origin offset variable area of the CNC system,thereby realizing the real-time compensation of the motion axis of the machine tool.According to the realization process of thermal error compensation and the construction method of the software and hardware framework of the error compensation system,the error compensation system is built,and the feasibility of the thermal error compensation method is verified.The error value can be predicted and the compensation signal can be output according to the collected swing head temperature and processing parameters,so as to complete the error compensation operation of the swing head.