Research On Analysis And Compensation Of Drilling Arm Positioning Errors Of Rock Drilling Rig

Rock drilling robot is an important equipment for modern tunnel excavation,with high drilling efficiency and good section adaptability.The precise positioning of the drill boom is an important basis for its realization of intelligence.During the positioning process of the drill arm,due to the comprehensive influence of various error factors,the actual pose of the drill rod end deviates from the theoretical pose,resulting in over-excavation and under-excavation,which affects the construction quality and production efficiency.In order to improve the positioning accuracy of the drill boom of the rock drilling rig,the error source analysis and error compensation research were carried out in this paper.The main research contents and results are as follows:(1)For the singularity problem of parallel joints,parallel joints were offset by adding translation joints.The kinematics model of the drill boom was established by the DH method.The correctness of the model is verified by using the MATLAB robot toolbox.A vehicle body positioning method based on two prisms was proposed,and a mathematical model of vehicle body positioning was established.The complete kinematic model from the end of the drill boom to the tunnel section was obtained,and the experimental verification was completed in the tunnel.(2)Through the error test experiment of drill boom positioning,the actual distribution law of each important error factor was obtained.According to the error test curve of the sensor,it is found that the detection error of the sensor after installation is greater than its detection accuracy.Through the end position error test,the actual error range between the theoretical model and the actual position was obtained.A new error was found,that is,the angle jump error at the junction of the telescopic arm,and the angle jump value was about 1～4°.The car body positioning error data shows that the car body origin error is less than1 cm,and the direction angle error is less than 0.9°.(3)The influence of each kinematic parameter of the drill arm on the positioning accuracy was simulated and analyzed.The results show that the joint rotation angle and joint torsion angle errors are amplified when they are transmitted to the end of the drill boom.Through the simulation analysis of the flexible deformation of the telescopic joint,it is found that the deflection and rotation angle of the main boom are relatively obvious.The principle analysis and error calculation of the angle jump at the joint of the telescopic arm were made.Three factors were found to have a large influence on this error.By analyzing the vehicle body positioning error,it is concluded that this part of the error is mainly concentrated in the transformation process of the vehicle body to the geodetic coordinate system.Through comprehensive analysis,a preliminary error compensation scheme was obtained.(4)Aiming at the problem of large positioning error of drill boom,error compensation and simulation analysis were carried out.The virtual joint was introduced,and the flexural deformation and jump angle error compensation model was established.A parametric error model coupling flexible deformation and vehicle body positioning was established.A selforganizing genetic algorithm was proposed to identify the optimal parameter error and compensate the position error of each part of the drill boom.By introducing the vehicle body positioning parameters,an error compensation model of RBF neural network was established,and the initial value of the network parameters was optimized by the improved genetic algorithm,which makes up for the limitation of the local search of the model.The simulation results show that the parameter error model method and the neural network error model method have better error compensation effect.(5)The error compensation models were experimentally verified.The flexural deformation and jump angle error compensation model can only compensate the position error in the height direction.Through the compensation of the parametric error model method,the error at the root of the boom is reduced by 21.7%,the error at the front end of the main boom is reduced by 56.1%,and the error at the end of the boom is reduced by 57.2%.Through SOGA-RBF neural network compensation,the position error of the root of the drill boom is reduced by 34.8%,the position error of the front end of the main boom is reduced by 74.9%,the position error of the end of the drill boom is reduced by 71.5%,the yaw attitude error is reduced by 65.0%,and the pitch attitude error is reduced by 65.0%.decreased by 61.7%.The results show that the two error compensation methods can effectively reduce the position error of each part of the drill boom and the attitude error of the end of the drill boom,and meet the requirements of practical engineering applications.