| Compared with specialized CNC machine tools,industrial robots have many advantages such as larger workspace,lower cost,and more degrees of freedom.The use of industrial robots for milling and removing complex surfaces of large components has broad application prospects in important industrial manufacturing fields such as aviation,aerospace,and molds,and has received high attention from the industry and academia.However,milling systems based on industrial robots have shortcomings such as low stiffness,variable stiffness,and low accuracy.If industrial robots are used for milling hard materials and large components,it is difficult to efficiently meet the machining accuracy and surface quality requirements.For example,the stiffness of articulated industrial robots is generally less than 1 N/μm.The stiffness of CNC machine tools is usually greater than 50 N/μm.This makes the milling removal load based on industrial robots not too large,which limits the improvement of the material removal processing rate;In addition,articulated industrial robots use multiple rotations around the joints to approximate the actual machining path.Any changes in the milling cutter posture along the machining path will cause changes in the configuration of articulated industrial robots,thus making the milling processing system based on articulated industrial robots variable in stiffness.The low and variable stiffness problems of industrial robots not only result in reduced machining accuracy and inconsistent force deformation along the entire machining path due to force deformation,but also lead to relative vibration between the milling cutter and the workpiece due to the reduced dynamic stiffness of the milling processing system(i.e.,poor dynamic characteristics).This thesis will mainly focus on the joint type industrial robot milling system with low stiffness and variable stiffness characteristics(hereinafter referred to as robot milling system),and is committed to studying the stiffness identification of robot milling system and the optimal control of milling robot posture based on static stiffness and dynamic stiffness(i.e.dynamic stability).The research content mainly includes the following.(1)A joint stiffness identification method for milling robots based on robot end displacement coupling and the dexterity index has been proposed.This method considers the coupling effect of translational and rotational displacement at the end of the robot,which can more accurately identify the stiffness value of the robot joint.Based on the proposed robot dexterity index,which can evaluate the distance between the robot’s current posture and singular posture.We have established the relationship between the stiffness matrix of robot joints and the Cartesian stiffness matrix,analyzed the impact of each joint on the dexterity index,and plotted contour maps of the dexterity index in the second and third joint spaces.Elaborated on the process of obtaining robot end displacement and obtained the deformation amount of the robot end.The stiffness value of the robot joint was obtained through the robot joint stiffness identification experiment,and its convergence gradually increases with the increase of the number of experiments.The small experimental error proves that the proposed joint stiffness identification method is feasible.(2)A method for optimal control of milling robot posture based on the static stiffness performance index has been proposed.A new robot stiffness performance index has been introduced to evaluate the normal stiffness of the machining surface,independent of the direction of external forces.The functional redundancy characteristics of robots were analyzed,and the robot pose was optimized based on redundant axis angles when milling on the same path.An optimization model for robot milling posture was established.The effectiveness and reliability of the proposed stiffness performance index have been demonstrated through robot milling validation experiments.The distribution law of stiffness performance index in robot workspace is analyzed.The contour map and 3D graphs of the stiffness performance index under different redundant axis angles are obtained.(3)A method for optimal control of milling robot posture based on dynamic stiffness characteristic index(i.e.dynamic stability index)has been proposed.This method does not require dynamic changes in milling parameters and is not dependent on the feed direction of the tool.The mechanism of mode coupling chatter was analyzed and the robot milling chatter model was established.The milling force model and the stability conditions for robot milling were introduced.An optimization model for robot dynamic stability posture was established.The frequency amplitude of the forces was analyzed,and the low-pass filtering algorithm was used to filter the forces.An orthogonal experiment was designed to identify the milling force coefficients.The Cartesian space dynamic stability validation experiment has proven that the proposed dynamic stability index can effectively evaluate the dynamic stability of robots in Cartesian space.(4)A method for optimal control of milling robot posture along a continuous tool path has been proposed.The optimization of the posture of milling robots was studied using the artificial bee colony optimization algorithm,with the objectives of static stiffness and milling dynamic stability.In the process of robot attitude control based on static stiffness and continuous tool path,the stiffness performance index and the changes in the optimal redundant axis angle were analyzed,and experiments have shown that this method can significantly reduce machining errors.In the process of robot posture control based on milling dynamic stability and continuous tool path,the changes in milling dynamic stability index and the optimal redundant axis angle were analyzed,and experimental results showed that this method can significantly increase the dynamic stability of robot milling. |
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