| The strength of the new titanium alloy TB18 can reach 1300 MPa,with high yield stress,heavy load and light weight and other excellent properties,is very suitable for the application of various thin-wall integral frame,beam and other structures in the aircraft.It is a new high-performance material in the field of aerospace in the future.Reasonable selection of processing parameters of TB18 is a problem that needs to be solved.The machining efficiency of thin-walled titanium alloy parts is low.In addition,the cutting force and cutting heat is high during the machining process.It is easy to produce deformation,which will affect the machining efficiency and surface quality of thin-walled parts.In view of the above problems,this paper mainly completes the following work:(1)Milling cutting force test.Taking axial cutting depth,radial cutting depth,feed rate and cutting speed as experimental variables,the orthogonal test of cutting force of tb18 titanium alloy was carried out.The influence of cutting parameters on milling force was studied by range analysis and variance analysis to optimize the value range of milling parameters.(2)Cutting force modeling of arc-angle end milling cutter.Based on the oblique cutting mechanism,the chip angle,shear angle and friction angle are theoretically predicted to solve the shear force coefficient and edge force coefficient.A cutting force model was proposed when the main cutting edge and the circular radius of the cutter tip were cut simultaneously,to study the influence of tool geometry parameters on the milling force,so as to adjust the feasible range of milling parameters under different circular radius of the cutter tip.(3)Finite element simulation analysis of milling deformation of thin-walled frame parts.ABAQUS three-dimensional finite element simulation technology was used to simulate the machining process of TB18 titanium alloy thin-walled frame parts,so as to explore the influence of cutting parameters on machining deformation.Four groups of different cutting parameters were used to cut thin-walled frames.The maximum deformation error of the test and simulation was compared to verify the accuracy and reliability of the simulation.(4)Optimization of milling process parameters considering cutting removal rate.Considering the machining surface quality and machining efficiency comprehensively,a parameter optimization model was established by using genetic algorithm with the maximum material removal rate as the objective function and the cutting force and maximum deformation as the constraint conditions.Exponential regression prediction model,BP neural network prediction model and GA-BP prediction model were used to predict the cutting force and the maximum deformation.The optimal prediction model was determined by error analysis,which was substituted into the constraint conditions of parameter optimization to optimize the cutting parameters. |
