Characterization Of 3D Roughness Parameters Of Milling Surface Morphology And Prediction Of Wear Resistance

High speed milling technology is helpful to improve product processing efficiency,and has been widely used in ship,automobile mold manufacturing and other industries.Under the influence of milling parameters,tool size and machine tool vibration,the machined surface will produce more complex texture morphology,which will affect the performance of parts.It is necessary to explore reasonable methods to characterize it,and the three-dimensional surface roughness parameters,as the most commonly used way to characterize the surface morphology,will undoubtedly increase the difficulty of characterization because of its variety.Therefore,the characterization parameters of surface texture morphology are simplified and subdivided by reasonable methods.It is of great significance to establish the relationship between them and surface functional characteristics for accurately and comprehensively characterizing the machined surface morphology and perfecting the three-dimensional surface functional characterization parameter system.Based on the simplified subdivision of the surface morphology of die steel materials Cr12 Mo V ball head milling,this paper comprehensively characterizes the machined surface morphology and quantifies the correlation between the characterization parameters and the surface wear resistance.The specific research includes the following parts:Firstly,the forming mechanism of the surface morphology of the ball head milling is analyzed according to the helical wire structure of the ball head milling cutter and the milling process parameters of the automobile cover die steel,and the analytical model of the surface morphology microelement characteristic parameters based on the static machining parameters is established;On the basis of the characteristic meaning of typical characterization parameters,the surface morphology is classified,which provides a theoretical basis for the simplified analysis of the characterization parameters and the characterization of the machined surface morphology.Secondly,by designing single-factor high-speed ball head milling test,the influence of machining parameters on surface morphology is explored,and then the three-dimensional morphology characterization parameter data are improved by digital filtering method.The variation of each characterization parameter of different types of morphology is summarized.On this basis,specific characterization parameters are selected for horizontal and vertical scale.Then,based on the grey system theory and the friction and wear test of the machined surface,the grey correlation model between the morphology characterization parameters and the wear quantity and friction coefficient is established,and the quantitative analysis of the correlation degree between the morphology characterization parameters and the wear resistance evaluation index is completed.Finally,using the method of BP neural network prediction,the prediction models of friction coefficient and wear amount based on morphology characterization parameters are established.The results show that the predicted value of the model is basically consistent with the measured value of the test,and the validity of the model is further verified.This method provides a certain basis for evaluating the functional characteristics of the machined surface.