Prediction Of Milling Stability And Optimization Of Milling Parameters For Titanium Thin-walled Parts

Thin-walled parts are widely used in the aerospace manufacturing industry,which has the characteristics of light weight and high strength.However,due to their low rigidity and weak damping,thin-walled parts are often not conducive to stable cutting during milling processing,and even cause chatter vibration,which ultimately affects the surface quality and machining efficiency of the workpiece.In the milling process of thin-walled parts,one of the main causes of chatter vibration is the regeneration effect.Therefore,the prediction of flutter in milling of thin-walled workpieces considering multiple factors is still a hot issue in academia and industry.Aiming at the problem of stability prediction during milling,a milling dynamics equation is established based on a fully discrete algorithm,and a multistep interpolation algorithm is used to discretize the delay term in the delay differential dynamics equation to study the milling stability prediction algorithm.By constructing the state transition matrix,the milling stability boundary is obtained according to Floquet theory,and the calculation accuracy and convergence rate of the algorithm are verified through simulation and comparison examples.Aiming at the process damping effect in the milling process,the mechanism of process damping was studied and the process damping force model was established.The process damping was used as an additional damping force to substitute the milling dynamic equations.Finally,the accuracy of the stability prediction model was verified by the milling stability experiment.Aiming at the parameter optimization of the milling,by establishing a multiobjective function,selecting reasonable machining parameter constraints and stable milling constraints as constraints,The multi-objective genetic algorithm is used to optimize the parameters,and the Pareto optimal solution set of the multiobjective function is obtained.Finally,the validity of the multi-objective genetic algorithm is verified by comparing with the empirical parameters.Finally,Aiming at the complexity of stability prediction and milling parameter optimization algorithms,a MATLAB / GUI platform was used to build a titanium alloy thin-walled part for milling stability prediction and parameter optimization system.The stability prediction and parameter optimization results were obtained by inputting relevant processing parameters.The system can provide a parameter scheme with a certain reference value for milling stability prediction and parameter selection in actual machining process.