Research On Cutting Specific Energy Prediction Model And Experiment In Milling

CNC machine tools are complex systems that combine machine,electric and liquid,which consume a lot of energy during production and processing.With the implementation of energy-saving and emission reduction strategies,the analysis and prediction of energy consumption of CNC machine tools has become an unavoidable problem in the field of modern green manufacturing.In this paper,the machine energy consumption prediction model based on milling experiment is established by data fitting.The influence of cutting parameters on the cutting specific energy is analyzed by the gray correlation analysis method.The MATLAB software is used to establish a cutting specific energy prediction model based on support vector machine to realize the qualitative and quantitative knowledge of numerical control processing energy consumption,so as to achieve energy saving and emission reduction and realize green manufacturing.The main work content is summarized as follows:First of all,in order to ensure the smooth progress of the research,a milling experimental platform was built,and the experiment was carried out by using the XD-40 A CNC milling machine,and the experimental data was obtained by the power analyzer.Analyze energy consumption characteristics and summarize the theoretical model of energy consumption.Based on the determined milling system,the influence mechanism of cutting parameters on machine tool energy consumption is analyzed.The cutting specific energy empirical model is analyzed,and the experimental data is used to fit,and the cutting specific energy prediction formula is obtained,and then the machine energy consumption prediction model is built.Then,introduce the theory of gray relational analysis and master the steps of its use.Based on the existing experimental platform,the required experimental data is obtained and substituted into the gray correlation analysis method to determine the optimal combination of cutting parameters.The gray relation number obtained is used to determine the cutting parameters that have the greatest influence on the cutting specific energy or the surface roughness and the order ofinfluence.Finally,aiming at the problem of establishing the numerical simulation of the numerical control machine tool,the number of experimental samples is small,and the variation of the predicted quantity changes greatly.A method based on support vector machine for cutting ratio prediction of CNC milling machine is proposed.The script file is written by MATLAB software and its combined LIBSVM toolbox.The parameters in the model are optimized and the cutting ratio of the machine under different machining parameters is predicted.Taking the No.45 steel of CNC milling machine as an example,the predicted value is compared with the experimental value.The mean square error of the model is 0.0094 and the correlation coefficient is 93.5%,which proves the feasibility of the model in predicting the cutting specific energy.