Research On Optimization Method Of CNC Minlling Parametes With High Quality And Low Vibration

With the continuous development and progress of the industry,cutting vibration has become one of the main reasons for limiting surface quality.The vibration generated during the metal cutting process not only reduces the surface quality of the processed product,but also affects the life,rigidity and reliability of CNC equipment and tools.How to reduce the cutting vibration generated during the cutting process of NC equipment has become a research hotspot at home and abroad.Aiming at the influence of the vibration generated by the CNC milling machine on the surface quality of the workpieces,this paper proposes to optimize the cutting parameters with the high surface quality and low vibration as the optimization goals.The choice of cutting parameters directly affects the vibration during the cutting process.In order to further explore the influence of cutting parameters on the vibration during the cutting process,this paper establishes a cutting process by establishing a dynamic signal analyzer,a CNC milling machine,and a PC end.Real-time cutting vibration acquisition system to collect and record digital vibration data.An experimental scheme for orthogonal experiments was designed.Using the established vibration data acquisition system and the VDF-850A CNC milling machine produced by Dalian Machine Tool Plant,a single-step groove dry cutting experiment was performed on No.45 steel,which is a material commonly used in the industry.Digital data of vibration in process.The results of range analysis and variance analysis of the experimental data show that the cutting depth has the greatest influence on the cutting vibration,followed by the feed speed and the spindle speed.The effect of cutting depth and feed speed on cutting vibration is extremely significant,and the spindle speed is significant.Finally,the least square method was used to fit the vibration data.The root mean square value of the cutting vibration was used as the dependent variable.The spindle vibration speed,cutting depth,and feed speed were set as independent variables.A mathematical model of cutting vibration was established.Lay the foundation for optimization research.In order to better study the influence of cutting parameters on the surface quality of the workpieces.Surface roughness measurement was performed on the processed No.45 steel workpieces.In order to study the influence of cutting parameter changes on the surface quality,the same analysis is performed on the surface roughness data of the workpieces for range analysis and variance analysis.The experimental results show that increasing the spindle speed can significantly improve the surface roughness of the workpieces,so it should be given priority Consider increasing the surface quality by increasing the spindle speed.The feed speed has a significant effect on the surface roughness,and the cutting depth has no significant effect on the surface roughness.The surface roughness data was fitted by SPSS software,and a mathematical model with surface roughness as the dependent variable and cutting parameters as independent variables was established to provide an optimized mathematical model for the realization of high-quality optimization research in milling.Considering the vibration generated during the cutting process and the surface quality of the workpieces,a multi-objective optimization mathematical model with high quality and low vibration as the optimization goals was proposed.In order to avoid that the two objective functions cannot reach the best at the same time,the weights of the two objective functions are determined by the analytic hierarchy process.A comprehensive objective function is constructed by using the sum-of-squares method,combined with the constraint conditions of the CNC milling machine and tool performance on the cutting parameters,to establish the comprehensive objective function optimization mathematical model.Using modern optimization algorithm Particle Swarm Optimization(PSO),the comprehensive objective function mathematical model is used as the mathematical model to be optimized,and optimization is performed to obtain the optimal combination of cutting parameters within the allowable range of cutting parameter constraints.In order to verify the accuracy,scientificity and effectiveness of the algorithm,the best cutting parameter combination obtained was used to verify the cutting experiments.The results show that compared with the empirical cutting results,using the particle swarm algorithm to optimize the cutting parameters for cutting processing,the cutting vibration RMS is reduced by 36%,and the surface roughness of the workpieces is reduced by 25%.The vibration during the machining process and the surface roughness of the workpieces,provide reference for the selection and optimization of milling parameters of the milling machine in actual engineering.