Dynamic And Static Characteristics Analysis And Optimization Of HKC6300 Horizontal Machining Center

High precision,high efficiency and high reliability are the mainstream direction of the development of machining and manufacturing at present.The dynamic and static performance of machine tools is closely related to the structure of machine tools,and directly affects the quality of processed parts.The traditional research and development methods that rely on experience and analogy have been unable to respond to the rapid development needs of the market in time.The application of CAD\CAE numerical simulation technology combined with optimization design theory to analyze and improve the structure of machine tools has become a hot spot in machine tool design research.Taking HKC6300 horizontal machining center as the object,this paper studies and analyzes the dynamic and static performance of the machine tool and its key components,puts forward the improvement scheme and makes reasonable optimization for the weak links of the machine tool.The main contents of this paper are as follows:(1)This paper summarizes the research status at home and abroad in the field of machine tool structure analysis and optimization,briefly describes the development history of structure optimization,and briefly introduces the principles and applications of size optimization,shape optimization,topology optimization,layout optimization and bionic optimization commonly used in the field of machine tool optimization.(2)Establish the key component model of HKC6300 horizontal machining center,and simplify the model reasonably.The load of the machine tool is determined by empirical formula.The static analysis,modal analysis and harmonic response analysis of the machining center are carried out to identify the weak parts of the machine tool,and the column is determined as the part to be optimized.(3)In order to maximize the stiffness and the first natural frequency of the column,the multi-objective topology optimization of the column is carried out based on the variable density method,and the column model is reconstructed according to the solution results.Then,according to the structural characteristics of the column,this paper designs additional cross shaped plate reinforcement and honeycomb like plate reinforcement,analyzes and compares the three types of plate reinforcement,and finds out the best choice.Finally,through the correlation analysis,the correlation matrix and sensitivity diagram between the column size parameters and the optimization objective are obtained,and the variables to be optimized are determined.(4)Based on the strong data fitting function of BP neural network and the superior nonlinear and discontinuous searching characteristics of genetic algorithm,the optimal solution of BP neural network and NSGA-? was determined.The optimal space filling design is used to obtain experimental design points for neural network training.The optimization program of BP neural network and NSGA-? algorithm is compiled in MATLAB,and the Pareto solution set is obtained,and the secondary optimization solution is carried out near the inflection point to complete the optimization of column.Finally,orthogonal experimental optimization method is used to optimize and compare with BP-GA algorithm,which verifies the superiority of BPGA algorithm.(5)Under the same conditions,the optimized column and the whole machine are simulated again,and the simulation results are compared with the performance parameters of the original prototype.According to the comparison results,it can be seen that the dynamic and static performance of the optimized machining center column and the whole machine is improved,and the machining accuracy and seismic performance of the machining center are improved.