Prediction On Surface Structure Of The Complex Ruled Surface In Flank Milling And Subarea Optimization Of Milling Parameters

The ruled surface is widely used in automobile ship,aviation engine,medical equipment and other industrial fields,due to the requirement of machining efficiency,five-axis CNC machine tool are often used for flank milling.However,the changing of cutter position and orientation during the flank milling process,and the existence of multiple errors,such as tool runout,tool deformation and vibration,it will seriously affect the surface quality of the machined parts,and further threaten the product performance and service life,so that the accurate prediction of the surface quality of machined parts is very important.Therefore,this paper puts forward a model for the surface structure prediction of flank milling ruled surface considering multiple error sources,and based on surface modeling distribution,the milling parameter optimization method of subarea strategy is proposed,it can be used to forecast and control the surface quality of complex surface,so as to provide a guarantee for the machining precision of the parts.The "S" shaped test specimen(hereinafter referred to as S specimen)is the newly proposed test standard for the accuracy of machine tools,it has geometric characteristics with variable curvature and variable concave and convexity,can be used as a typical complex curved surface part.Therefore,the research object of this paper takes S specimen as an example to carry out the application and verification work of surface structure prediction and milling parameter optimization.The main works of this paper are summarized as follows:1.A prediction model for surface structure of flank milling ruled surface is established.By analyzing the space point cloud data of tool relative to ruled surface motion trajectory,an improved Z-map model is proposed to realize the mesh generation of ruled surface,so as to establish the local bounding box based on mesh node,and to complete the extraction of the surface structure feature point with the spatial point cloud data.The set of all mesh feature points composes the surface structure of ruled surface,and the surface structure prediction of arbitrary ruled surfaces is achieved.2.The surface structure prediction and influencing factor analysis of S specimen.Based on the tool path trajectory information of S specimen,the milling force analytical model of flank milling S specimen is established.Through the parameter identification of the machine tool-tool dynamics system,we can obtained the tool deformation and the vibration displacement under the whole path,and connecting with the tool runout errors to realize the prediction of S specimen surface structure.Then the shape error and roughness profile were separated by Gaussian filter,and the accuracy of simulation results was verified by milling experiments.Finally,the influence of milling parameters on the surface structure was analyzed.3.The milling parameters optimization method based on surface subarea strategy is presented.In the different areas,with the shortest processing time and the best processing quality as the objective functions,with maximum instantaneous force and milling stability as the constraint conditions,the particle swarm optimization algorithm is applied to perform optimization,thus the different milling parameters of high efficiency and economy are obtained.Finally,the S specimen is taken as an example to compare the processing quality before and after the optimization of the parameters,and the experimental results show that S specimen surface quality is improved,which proved the feasibility of the optimization method.