Optimization Of Rough Machining Based On Complex Surfaces

With the rapid development of science and technology,there are more and more types of industrial parts or home decorations containing complex curved surfaces,and the requirements for processing efficiency,processing quality and precision of these products have also increased.So effectively solve the complex surface products of high efficiency,high quality,high intelligence and other CNC machining problems have been widely concerned and research.To this end,this paper studies the optimization and planning method of high-efficiency rough milling of complex curved surfaces with circular saw blade as milling tool,which aims at high efficiency machining and high average material removal rate.Firstly,the method of obtaining 3D complex surface graphic data information from STL graphic files is studied,and the geometric characteristics of circular saw blades and the method of selecting circular saw blade specifications are analyzed.At the same time,a hole repair and optimization method is proposed for some surfaces containing holes,which facilitates the acquisition of tool point information for subsequent roughing planning with circular saw blade tools for milling.Secondly,in order to solve the problem that complex surfaces are difficult to process or have low processing efficiency,this paper uses clustering algorithm to divide complex surfaces into regions.At the same time,according to the problems of low accuracy of clustering results and unstable surface division results caused by the inability to determine the initial clustering center in the process of surface region division by the clustering algorithm.An improved K-means clustering algorithm based on weight and probability(WPK-means)is proposed to optimize the initial clustering center point.First,the information on the surface data points of a complex surface is taken as a sample,and the density information of each sample point determined by weighting the distance between the sample points in the sample.Then,the optimal initial clustering center is selected according to the density information and probability function settings of each sample point,and it is involved in the K-means clustering algorithm process to ensure high accuracy of each clustering result.In the end,the clustering algorithm in this paper is used to classify different types of data sets,and verify the effectiveness of the clustering method proposed in this paper.Again,in order to further improve the milling efficiency of complex curved surface,based on the division of complex curved surface area,the average material removal rate is taken as the evaluation index.The optimization method of cutting direction of multiple surfaces after surface region division and the path planning method of some special-shaped surfaces are proposed.At first,the partitioned surfaces after zoning are grouped according to their axis span in the spatial coordinate system.Then,by searching the longest curve in the surface,the inclination angle of the plane where the longest curve is located is used as the optimal direction to travel on the surface,reducing the number of tool entry and exit and shortening the roughing time.At the same time,for some special-shaped surfaces,the parametric line method is used to discretize the complex surface area,And the non-iso parametric path planning is carried out according to the geometric characteristics of the surface and the circular saw blade characteristics to obtain the tool position points for milling processing.Lastly,the tool direction optimization method and special-shaped surface path planning method are compared with other traditional surface machining methods to verify the effectiveness of the proposed optimization and planning methods.Finally,the model of AC double rotary table 5-axis CNC machine was built in VERICUT simulation platform,and the circular saw blade type tool model was constructed.Following that,the planned tool point information is converted into CNC machining code by the machine tool forward and reverse kinematic transformation,and simulated roughing of complex surfaces in VERICUT software.At the same time,the converted machining code was used for actual milling roughing experiments on an AC dual rotary 5-axis CNC machine,and the actual machining results were observed.In the end,the mouse model and the shaped surface model were subjected to simulation machining experiments and actual milling experiments,and the feasibility of the optimization and planning method proposed in this paper is verified.