Machining Simulation And Machining Parameter Optimization Of Aeroengine Compressor Blade

In order to reduce the processing cost and improve the processing efficiency,the machining process simulation of a complex thin-walled aero-engine compressor blade was studied.The reasonable processing technology was formulated.Combined with the cutting simulation theory,the milling force of the blade processing was analyzed.The optimization of machining parameters was realized on the condition of both machining efficiency and machining quality,and a more accurate optimization result was obtained.The main work completed in this thesis is as follows:Firstly,the structure and material characteristics of the blade were analyzed,and the advantages and limitations of the common machining methods for complex curved parts were compared.The blades were processed on a five-axis computer numerical control(CNC)machine tool platform.Based on the main parameters of the selected machine tool and the motion law of each axis,the mathematical model of machine tool motion was established to prepare for post-processing customization.Secondly,based on the formulation principle of the machining process route,the machining process route of the blade was formulated to realize the reasonable planning of the tool path.Taking UG as the platform,the machine tool post-processing file was customized based on the post-processing algorithm and the mathematical model of machine tool movement established.The tool path of blade machining was transformed into NC program.The feasibility of blade machining technology was verified through the virtual machine tool system and the total processing time was obtained.The simulation model of the five-axis CNC machine tool was built,and the movement axis,control system and other parameters of the machine tool were configured.The rationality of the blade machining technology was verified by simulation tests.Thirdly,the mathematical model of blade milling force ws established by combining finite element method and multiple regression analysis.Finite element method was used to simulate the cutting of blades in the semi-finishing stage,and the curves of milling components in each direction were obtained.Based on these curves,the milling force peaks were obtained,and the influence of machining parameters on the milling force was analyzed.Multivariate regression fitting method was used to fit the milling force data into an accurate prediction model of the milling force.The accuracy of the mathematical model of the milling force was verified by comparing the calculated and simulated values of the milling force under the original machining parameters,which was used as the basis for the subsequent machining parameter optimization.Finally,in view of the current thin-walled parts processing deformation and low processing efficiency,an optimal mathematical model considering the processing efficiency and milling force changes was proposed.Material removal rate and milling force were taken as two optimization objectives.Aiming at the limitation that the traditional genetic algorithm could not directly reflect the relationship between material removal rate and milling force change,an improved genetic algorithm was adopted to optimize the objective function.According to the requirements of different processing stages,the Pareto solution sets of various optimal results were obtained,and the results of the optimization scheme and the original scheme were compared to verify the practicability of the optimization model,which can provide a reference for the actual processing.