| Virtual manufacturing technology developed rapidly with the rapid development of computer technology, and the great importance attached by the people. Virtual CNC lathe is based on virtual manufacturing ideological and theoretical Machining Simulation. During Virtual CNC lathe simulation, cutting power forecasts and cutting parameters choice is a very important element. Cutting force direct impact on cutting heat, tool wear and durability, parts machining precision machined parts and the surface quality is on the basis of physical simulation. Then the selection and optimization of cutting conditions has an important impact on cutting productivity, processing quality and costs. Therefore, accurate prediction of cutting force, a reasonable choice of cutting parameters to be key for ensure processing quality and increase productivity.This paper briefly describes the system of virtual processing entity modeling methods and virtual architecture CNC Turning and modeling requirements. Technology research make a target on CNC turning the cutting force and parameter optimization.Metal-cutting process is very complex, there are many influence factors. Before a long time, Chinese and foreign scholars on the cutting force of a theoretical model of a lot of work, but is still not match the actual cutting and the theoretical formula. Thus, in practice only used by the experiment is the empirical formula for cutting force projections. Lately the artificial neural network research and applied research on the rise, cutting force to achieve accurate prediction of a strong approach.In this paper, in response to the source of cutting force, influencing factors and the analysis of the methods of forecasting at the same time, they are theoretical formula and BP neural network technology to predict the cutting force. Forecast results with the experimental values error comparative analysis found that the theoretical formula forecast error is less than 5% will be able to meet the requirements of prediction accuracy; BP neural network prediction error exception of a few points more than five percent, other values are less than 5%, and some can even achieve a margin of error of 0.44 percent, a very high prediction accuracy will be able to meet the requirements of high-precision forecast. Based on the above two forecasting methods, the use of MATLAB GUI user controls on the cutting force projection software design, the software is simple, accurate forecasting results, so that the users can facilitate the processing of the master before cutting force data.Papers using finite element analysis method forecast work piece machining precision, and gives theoretical test. The method easily through computer programming operations, especially against some of variable cross-section of the work piece machining accuracy of forecasts more convenient, can effectively replace the traditional formula for calculating deflection in the deformation of the work piece machining forecast predictable speed, high accuracy advantages. In addition, the paper also uses finite element analysis software ANSYS analysis of the process of cutting the work piece cutting force caused by deformation processing, and gives the corresponding conclusions.In the selection of the cutting process parameters, cutting conditions for and optimization has an important impact on cutting production efficiency, processing quality and processing costs, Based on the limited cutting force caused processing deformation analysis, application BP neural network technologies to meet parts machining accuracy as the goal, cutting parameters to optimize, optimize the error within 5 percent to meet the parameter optimization purposes. |
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