| Compared with CNC machine tools,robots have the advantages of high flexibility,low cost,wide range of processing,and strong ability of parallel and coordinated operation,so the application of robots in the field of machining is gradually increasing.However,due to the characteristics of its multi joint series structure,industrial robots have two disadvantages: low absolute positioning accuracy and weak stiffness,which seriously restricts the application of robots in the field of high-precision manufacturing.Therefore,solving the contradiction between robot low precision,weak rigidity and high precision machining of complex parts is a research hotspot in the field of robot machining.In this paper,to solve the two problems of low absolute positioning accuracy and weak stiffness in robot milling,an on-line compensation method for robot milling error is proposed,which can simultaneously compensate the positioning error caused by robot kinematic parameters and the deformation error caused by joint flexibility.Firstly,the kinematic characteristics and stiffness characteristics of the robot are analyzed to lay the foundation for the subsequent error compensation.Then,an on-line compensation method for robot milling error is proposed to improve the precision of robot milling.Then,in order to reduce the time delay of online compensation algorithm,based on the self-tuning incremental PID control algorithm,the compensation value is adjusted to improve the real-time performance of the compensation algorithm.Finally,milling experiments are carried out to verify the effectiveness of the compensation algorithm.The main contents of this paper include:(1)To solve the problem of low positioning accuracy in robot milling,the geometric parameter calibration experiment is studied.Firstly,the kinematics model of the robot is established based on DH model,and the established kinematics model is analyzed and verified;Then,based on the principle of minimum position error,the calibration model of parameter error is established,and the kinematic parameters of the robot are calibrated by the least square method;Finally,the joint angle compensation method is used to compensate the robot positioning error,and the compensation results are analyzed to verify the accuracy of kinematic parameter calibration results.(2)In order to solve the problem of joint flexible deformation in milling,the stiffness characteristics of robot are studied and the influence of robot stiffness on milling deformation is analyzed.Firstly,the relationship between joint flexibility and Cartesian stiffness matrix is established based on the classical static stiffness mapping model;Then,the joint stiffness is identified based on the recursive least square method;Then,the experimental scheme of stiffness identification is proposed to obtain the joint stiffness,and the stiffness identification results from multiple dimensions are analyzed;Finally,the overall stiffness and milling deformation error of the robot are analyzed.(3)In order to improve the accuracy for robot milling,an online error compensation method is proposed to solve the problem of positioning error and deformation error in robot milling.Firstly,the calculation method for robot milling error is studied;Then,based on the real-time milling force,an error compensation method is proposed.The coupling relationship between the compensation value and the deformation value in the compensation process is considered in this method,and the compensation value satisfying the accuracy requirement can be calculated at one time;Finally,in order to reduce the influence of time delay in the compensation system,the compensation value is optimized and adjusted based on the selftuning incremental PID control model.(4)In order to verify the effectiveness of on-line milling error compensation algorithm,related experiments are carried out.Firstly,an experimental platform is established to verify the accuracy of the empirical formula of average milling force;Then,the distribution of positioning error and deformation error in specific machining cases is analyzed based on error prediction method;Finally,according to the error compensation scheme,the compensation system experimental platform is established,and the corresponding software control program is compiled to verify the effectiveness of the algorithm. |
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