Prediction Of Milling Deformation And Optimization Of Process Parameters Of Aluminum Alloy Thin-walled Structural Parts

Aviation aluminum alloys play an increasingly important role in the manufacture of aviation aircraft due to their excellent comprehensive physical and mechanical properties.However,due to the coupling of multiple factors,large-scale thin-walled aviation structural parts are prone to machining deformation,which greatly affects the production efficiency and cost of aviation products and limits the development of my country's aviation manufacturing industry.This article is supported by the school-enterprise cooperation project "Research on the Processing Technology of Deep and Narrow Ear Slots for Aircraft Joint Parts".Based on the analysis of the factors affecting the deformation of aluminum alloy aviation thin-walled structural parts(material properties,structural characteristics,initial residual stress of blanks,process parameters,clamping,etc.),research on the prediction and control of machining deformation of aluminum alloy thin-walled parts.And complete the corresponding process parameter optimization to provide a strategy for the processing deformation control of aluminum alloy thin-walled structural parts.In order to obtain the initial residual stress distribution law and its effect on the deformation of thin-walled parts,an automated residual stress testing system was developed based on the crack compliance method.The initial residual stress test was carried out on the aluminum alloy 7050-T7451 thick plate to obtain the distribution law of the internal initial residual stress with the thickness change,and the function relationship between the residual stress and the plate thickness was established by Gaussian fitting.The FORTRAN language is used to develop a subroutine of the functional relationship between the residual stress and the thickness of the blank,which is used to apply the initial residual stress in the subsequent finite element simulation analysis.The orthogonal milling experiment of aluminum alloy 7050-T7451 under different processing parameters was designed to obtain the cutting force and cutting temperature data under different parameters.The linear regression analysis method is used to fit the empirical formulas of milling force and milling temperature to provide a data basis for subsequent finite element simulation.The finite element simulation model of T-shaped thin-walled parts is established by ABAQUS,the thermal-mechanical coupling factors are considered,and the initial residual stress,milling force and milling temperature are applied to the finite element model to obtain the final deformation data.The milling experiment of T-shaped thin-walled parts under the same conditions was carried out,and the deformation of the work-piece was measured by a coordinate measuring machine,and compared with the simulation data to verify the accuracy and effectiveness of the finite element model.On this basis,the finite element method is used to study the influence of machining sequence on machining deformation,and the optimal machining sequence suitable for T-shaped thin-walled parts is determined.Using the established finite element model,the law of deformation changes with process parameters is revealed,and a data basis is provided for the subsequent deformation prediction and parameter optimization.Taking the deformation data under different parameters obtained by the finit e element simulation as samples,the BP neural network technology was used to establish the machining deformation prediction model and verify the accuracy of the model.Combining neural network technology and genetic algorithm technolo gy,the process parameters are optimized with the deformation prediction model as the objective function,and the best process parameters are determined when t he processing deformation is minimum.