Research On Milling Stability Optimization Considering The Uncertain CNC Machine Tool Machining Position

As one of the basic common technologies of advanced manufacturing technology,high speed milling is widely used in aviation,aerospace,energy,rail transportation and metal milling fields and so on,having a broad application prospect.In the milling process,the severe vibration(milling chatter)occuring far lower than the rated power can decrease the machining accuracy and efficiency,affect the service life of cutter and computer numeral control machine tool,and cause the computer numeral control machine tool to play its main advantages.Therefore,the problem of milling stability caused by regenerative chatter has been focused on the current research,which is very significant for the engineering application of machine tool.However,the traditional milling stability research has not considered the influence of machining position and feed direction changes on the tool tip frequency response functions,which leads to the uncertain prediction of milling stability lobes and chatter-free milling parameters.In order to solve this problem,the processing system has been used as the research object,and the milling process dynamic modelling,the milling stability prediction and the milling parameters optimization have been studied.The main research contents are as follows:Firstly,the milling process dynamic modelling and milling stability prediction method have been studied.The dynamic model considering the transient milling thickness has been established,and the influence of the feed direction has been introduced on the basis of the traditional milling stability prediction principle.Based on this,the milling stability lobes can be obtained accurately,which lays a foundation for the machining parameters selection.Then,how the machining position,feed direction and milling parameters affect the milling stability and how to obtain the stability diagram when these factors change have been discussed.On this basis,a method for studying the milling stability in the generalized manufacturing space of the machine tool based on orthogonal experiment has been proposed.The orthogonal experiment method has been used to design different process schemes,and the tool tip frequency response functions for each scheme have been obtained through the impact testing.Then,the milling stability analysises has been performed to obtain the sample information of the parameters representing the milling stability,in which the machining position,feed direction and milling parameters have been taken as the variables.Finally,the milling stability prediction and optimization method based on the support vector regression machine and genetic algorithm has been studied.A support vector regression prediction model for predicting the milling stability in generalized manufacturing space has been established,and its prediction accuracy has been verified by the milling test.Then,the dynamic evolution law of milling stability in the machine tool working space can be studied through the support vector regression prediction model.Furthermore,an optimization model has been established and solved by the genetic algorithm to obtain the optimal process parameters with the maximum material removal rate in the generalized manufacturing space.The accuracy of the predicted optimal configuration of the milling parameters has been verified by milling test.