平行双关节坐标测量机的结构参数标定  

Structural Parameter Calibration for Parallel Dual-Joint Coordinate Measuring Machine

作　　者：董钊[1] 张炜[1] 赵会宁[1] 于连栋[1] 

机构地区：[1]合肥工业大学仪器科学与光电工程学院,合肥230009

出　　处：《纳米技术与精密工程》2015年第4期287-292,共6页Nanotechnology and Precision Engineering

基　　金：国家自然科学基金资助项目(51375137)

摘　　要：平行双关节坐标测量机(PDCMM)是一种3自由度、高精密、可现场测量的测量仪器.为了提高平行双关节坐标测量机的测量精度,采用粒子群优化(PSO)算法对其结构参数进行标定,避免了最小二乘法(LSM)在求逆和求偏导数时产生的计算误差.基于Denavit-Hartenberg(D-H)模型对平行双关节坐标测量机建立运动学模型和误差模型,以不同位置实际值和测量值之间的残余误差平方和作为PSO算法的目标函数,优化结构参数.实验结果表明,PSO算法具有标定精度高和收敛速度快的优点,可以有效提高平行双关节测量机的测量精度.Parallel dual-joint coordinate measuring machine （PDCMM） is a 3-DOF, high precision, and in-situ measuring instrument. To improve the measuring accuracy of PDCMM, particle swarm optimization （PSO） algorithm was introduced to calibrate the structural parameters, which avoided the calculation er- rors resulting from the inversion and partial derivative of least square method （LSM）. The kinematic model and error model of PDCMM were established by using Denavit-Hartenberg （D-H） model. The sum of the square of residual errors between actual and measured values at different positions was supposed to be the objective function of the PSO algorithm. Experimental results demonstrate that the PSO algorithm has the advantages of high calibration accuracy and fast convergence speed, effectively enhancing the measuring accuracy of PDCMM.

关 键 词：平行双关节坐标测量机 结构参数标定 D-H模型 粒子群优化算法 

分 类 号：TH721[机械工程—仪器科学与技术]