Modeling Of Energy Consumption And Optimization Of Process Parameters In Complex Surface Milling

With the progress of science and technology,energy conservation and emission reduction has attracted a lot of attention.The continuous development of the manufacturing industry leads to huge resource consumption,which is the key object of national energy conservation and emission reduction,and green manufacturing development.The production and manufacturing of parts mainly depend on the operation of CNC machine tools.Therefore,setting reasonable processing schemes and optimizing process parameters for parts is one of the main ways to reduce resource consumption.The modeling of energy consumption in the milling process of CNC machine tools is the premise to reduce resource consumption in parts processing.Based on the key project of international(regional)cooperation and exchange of the National Natural Science Foundation of China and the project of the Heilongjiang Natural Science Foundation team,this paper studies the energy consumption and process parameter optimization of complex surface milling of titanium alloy materials.The main research contents are as follows:First of all,according to the no-load energy consumption characteristics of VMC-C50 five-axis CNC machine tools with double turntables,this paper establishes the no-load power consumption models of the spindle,feed axis,rotary axis,and swing table of CNC machine tools respectively,and proposes the linear relationship between the no-load power of the spindle and the spindle speed,and the relationship between the no-load power consumption of the feed axis and the feed speed.It is found that in each speed segment,the spindle power increases with the increase of speed,and basically follows a linear relationship.The relationship between the feed shaft power and the feed speed is nonlinear.Secondly,based on the curvature characteristics of complex surfaces,the energy consumption models of milling power and driving power per unit volume are established by using the Gauss curvature formula.Based on the energy consumption model,the energy consumption field model of the CNC milling path is established by introducing "specific energy".By analyzing the energy consumption field of the tool location in the machining path and the simulation and experimental values of the energy consumption field of the milling path,the energy consumption distribution of each tool location and the machining path,as well as the internal relationship between the curvature of the surface and the energy consumption field distribution,are known.Finally,the accuracy of the model is verified by milling experiments on a five-axis CNC machine with double turntables.Thirdly,based on the curvature characteristics,the influence characteristics of different milling parameters on the processing energy consumption,surface roughness,processing efficiency,and tool life of complex surfaces are analyzed.Using the gray relational analysis genetic algorithm based on a neural network,the optimization objective functions of processing energy consumption,surface roughness,processing efficiency,and tool life are established respectively,and their data are optimized to find the optimal solution,The superiority of the optimization algorithm is verified by experiments.Finally,according to the above-established energy consumption model and milling process parameter optimization model of the CNC machine tool milling process,the energy consumption prediction and optimization platform for the complex surface milling process is established.The feasibility of the energy consumption prediction and optimization platform is verified through the milling experiment of complex surfaces,which provides scheme support for the selection of milling process parameters with low energy consumption and high efficiency in the milling process of complex surfaces.