Research On The Springback Of Titanium Alloy Machined Surface Based On DIC

In this paper,the springback deformation of titanium alloy during cutting process is taken as the research object.The influence of different cutting parameters on the springback deformation is analyzed by using the cutting finite element simulation and the experiment of springback detection under the condition of titanium alloy dry milling The optimal tool structure is obtained by using two-dimensional cutting simulation with the goal of reducing the springback deformation.Finally,the prediction model of machining parameters and the springback of machined surface is obtained by combining the BP neural network modeling.It can provide theoretical guidance for vibration reduction of titanium alloy cutting.(1)Two dimensional cutting simulation of titanium alloy springback.In order to solve the problem of the springback on the machined surface of titanium alloy in the cutting simulation environment,this paper uses two-dimensional cutting of titanium alloy to complete the simulation,and completes the theoretical calculation of the springback in this environment based on the principle of tribology..By changing the cutting speed and the axial cutting depth,the calculation of the springback of the machined surface of titanium alloy under the simulation environment is completed,which provides the theoretical basis for verifying the accuracy of online measurement of the test.In the cutting simulation environment,the influence of different tool structures on the springback deformation of the machined surface of titanium alloy is analyzed.By synthesizing the influence of different cutting parameters,the tool structure with the least springback is obtained.(2)Measurement of rebound deformation of Ti6A14V titanium alloy based on DIC Aiming at the influence of different machining parameters on the springback of machined surface,several orthogonal experiments were designed to dry mill titanium alloy with carbide tool at low speed.Using binocular camera to monitor the processing of titanium alloy,and based on DIC method to calculate the springback of the machined surface of titanium alloy.DIC method is to collect the speckle image sequence of black-and-white speckle on the tested sample in the process of deformation by binocular camera,and store the recorded gray information in the form of matrix in the computer for relevant calculation.According to the experimental results,the correlation model of the axial cutting depth ap,spindle speed n and feed rate f of the cutting parameters on the springback of the machined surface is obtained(3)The establishment of prediction model of the springback.In order to further study the springback deformation in high-speed milling experiment.BP neural network is introduced into the experiment of titanium alloy dry milling.It is used to study the influence of cutting parameters(axial cutting depth ap,spindle speed n and feed rate f)on the springback of machined surface.The prediction model between the springback of cutting parameters is established.The results show that the accuracy of the prediction model is high,which can provide theoretical basis for the subsequent experiments.