Research On Process Optimization And Simulation Of Multi-robot Cooperative Machining For Large Blade

Large blade parts are more and more widely used in aerospace,ship and energy fields.This kind of parts belong to large and complex free-form surface,which has complex shape,large curvature change,high degree of spatial distortion and thin-walled structure,so it is very difficult to process.Multi-axis milling technology and its processing equipment have become an effective means to solve the processing of large blade parts.However,the current research on the machining quality and efficiency of large blade parts mainly focus on the multi-axis CNC milling process plan,tool rail planning,cutting parameter optimization and other aspects.Less research is conducted from the perspective of new processing technology supporting multi-task collaboration and optimization of its key process links,which makes it impossible to solve the problem of low material removal rate and processing efficiency in the finishing process more effectively.In this thesis,the mixed-flow turbine blade is taken as the research object.For the problem of variable curvature,large distortion profile and the difficulty of improving the multi-axis CNC milling precision,a large-blade multi-mechanical arm collaborative machining method is proposed,and the process scheme is developed,and the key process links are analyzed and optimized.Firstly,the main process parameters,the cutting behavior,the finishing efficiency and the main influencing factors in the process of large-blade multi-mechanical arm co-milling were analyzed.The multi-mechanical arm collaborative machining scheme of turbine blades was developed,and the key process parameters optimization calculation method was given.On this basis,the multi-mechanical arm coordinated processing layout optimization was completed.Then,for the most difficult-to-machine surface of the turbine blade,the profile characteristics were analyzed.The feasible region of tool axis characteristics was quantitatively described by the forward inclination angle and the lateral inclination angle relative to the center points of different curvature parameter lines on the surface,and the optimization model of the characteristic tool path of the inlet edge based on the forward inclination angle and the lateral inclination angle was established.The genetic algorithm is used to find the optimal tool axis vector adaptively,which can effectively improve the tool path milling of large blade inlet water edge.Next,according to the characteristics of multi-surface and multi-curvature region of blade,a task allocation model for multi-curvature surface collaborative machining was established and optimized.Finally,the simulation environment of large blade multi-mechanical arm co-processing was builtand the process plan,the key process links and the task assignment model were simulated and analyzed.The effectiveness of the overall plan for large blade multi-mechanical arm co-processing technology was verified.The research results of this thesis provide a theoretical and a method reference for the development of large-blade multi-mechanical arm collaborative processing schemes,which is of great theoretical significance and production application value for improving the efficiency and quality of large-scale blade finishing.