Optimization Analysis Of Milling Processing Parameters Of Aluminum Alloy 7050-T7451T Thin-walled Parts

Compared with other material parts,aluminum alloy thin-walled parts have the characteristics of good load-bearing,light weight and high specific strength,so they are widely used in aerospace industry.During the actual milling process,the aluminum alloy thin-walled parts are very easy to process deformation and cause the failure of machining.The machining quality and machining precision of the aluminum alloy thin-walled parts can not be guaranteed during the actual milling process.There are many reasons for machining deformation of thin-walled aluminum alloy parts,and improper selection of milling parameters is one of them.The selection of milling parameters in the past very long time depends on the experience of field processing,and there is no reasonable selection range of milling parameters.This will easily lead to the low processing efficiency of thin-walled parts,and the deformation of parts can not be effectively controlled,and the processing precision of thin-walled parts can not be met.At present,the research on the milling of aluminum alloy thin-walled parts has been more mature.However,most of the analysis and research neglected the effect of milling parameters on the deformation of aluminum alloy thin-walled parts,which leads to the failure of the selected milling parameters to meet the effective milling of aluminum alloy thin-walled parts.In this paper,in order to solve the problem of machining deformation easily during the milling process of aluminum alloy thin-walled parts,based on metal cutting principle,elastic plastic mechanics and finite element simulation technology,the orthogonal experiment of aluminum alloy 7050-T7451T thin-walled parts milling is designed.The dynamic cutting force of three dimensional dynamic cutting by KISTLER frequency frequency response is carried out.The cutting force is measured in three directions of X,Y and Z in milling process.The cutting force model is established.Finite element analysis software ABAQUS is used to establish a finite element simulation model of aluminum alloy thin-walled parts milling.The milling process of aluminum alloy thin-walled parts is studied.The correctness of the finite element model is studied.The size and change trend of the cutting force and the deformation amount in the milling process are studied and analyzed.At the same time,the relationship between the cutting force and the deformation amount is established by the least square method.According to the principle of neural network,the function relation between milling parameters and processing deformation quantity is constructed,and the BP neural network model is established to predict the deformation of machining.The minimum processing deformation quantity and maximum machining efficiency of aluminum alloy thin-walled parts are used as evaluation target by using genetic algorithm,and the minimum processing deformation amount and maximum addition are established respectively.The target function of working efficiency is used as a constraint condition for machine tool power,machine tool parameters and actual milling conditions.The four milling parameters of spindle speed N(r/min),feed per tooth fz(mm/z),axial cutting depth ap(mm)and radial cutting depth ae(mm)are optimized and improved,and the target conditions are found.The optimal combination of milling parameters provides guidance and reference for milling 7050-T7451T aluminum thin-walled parts.The main research work of this paper is as follows:(1)According to the principle of metal cutting,the orthogonal experiment was designed for the milling of aluminum alloy 7050-T7451T thin-walled parts.The cutting force model was established and the validity of the model was verified by calculation.(2)Based on the elastic plastic mechanics and the finite element simulation technology,the finite element simulation model of the aluminum alloy 7050-T7451T thin-walled parts milling is established,and the correctness of the finite element model is verified by the experiment.(3)According to the neural network theory,the nonlinear relation between the milling parameters and the processing deformation is constructed by the MATLAB mathematical analysis software,and the BP neural network is established to predict the deformation of the aluminum alloy thin-walled parts,and the correctness of the prediction model is verified.(4)using the genetic algorithm,the minimum processing deformation quantity and the maximum machining efficiency of aluminum alloy thin-walled parts are used as evaluation targets.The objective function of minimum processing deformation quantity and maximum machining efficiency is set up respectively.The power of machine tools,machine tool parameters and actual milling conditions are used as constraints,and the spindle speed N(r/min),Four milling parameters of each tooth feed fz(mm/z),axial cutting depth ap(mm)and radial cutting depth ae(mm)were optimized to find the optimal combination of milling parameters satisfying the target conditions.