Research On Intelligent Control Technologies Of Automatic Grinding And Polishing For Complex Shaped Workpieces

With the rapid development of industrial automation technology and the improvement of people's living standards,the demand for various complex shaped parts is increasing.In order to meet the requirements of the quality and quantity of complex shaped parts,and break through the traditional processing methods of grinding and polishing parts to develop a new ultra-precision automatic grinding and polishing process that can improve work efficiency and product quality,reduce product costs,it has become an important problem in the field of complex shaped surface processing and manufacturing.Therefore,in this paper,we carry out research on the intelligent control of automatic grinding and polishing of complex special-shaped workpiece,and respond to the layout of intelligent manufacturing strategy and enhance the level of polishing and grinding of complex special-shaped workpiece.so,research and development automation polishing technology not only has a high academic value,but also has considerable practical significance.This paper consulted a large number of domestic and foreign industrial robot technology based on automatic polishing polishing literature.Research on the grinding and polishing technology of robots in related universities and research institutes at home and abroad has made great progress.Based on the existing research results,the author makes a deep research and analysis on the intelligent control technology of robotic grinding and polishing of complex shaped parts.First,the author summarized the research status of robot grinding and polishing technology at home and abroad,and introduced the robot grinding and polishing system,including its hardware composition and the main function of each part,and elaborated the working principle of the system;Combined with grinding and polishing process requirements designed to polish the polishing process flow chart.Then,we studied the optimization of the grinding parameters of the robot,and established the material removal rate model and the material removal profile model which based on the detailed analysis of abrasive grain distribution and the material removal mechanism of the abrasive surface.The simulation analysis and experimental research methods are used to analyze the influence of grinding and polishing parameters on surface roughness emphatically.Secondly,the author studied the control strategy of the grinding robot,and designed a controller based on the RBF neural network to do simulation and experiment of the compensation of the grinding robot system.Finally,it is proved that the RBF neural network controller can improve the control effect and meet the performance requirements of the system.Finally,the robot grinding and polishing trajectory planning is studied,based on classical analysis of parameter line method,Hilbert filling curve method and cross-section method and so on,the arc length optimization algorithm based on NURBS curve and surface differential equation is summarized and derived.