新型5自由度并联机床运动学自标定研究  

Kinetic self-calibration of novel 5-DOF parallel machine tool

作　　者：高建设[1] 程丽[1] 赵永生[1] 

机构地区：[1]燕山大学机械工程学院,河北秦皇岛066004

出　　处：《计算机集成制造系统》2007年第4期738-743,共6页Computer Integrated Manufacturing Systems

基　　金：河北省自然科学基金资助项目(503287);河北省博士基金资助项目(2001216)~~

摘　　要：为提高并联机床的运动精度,提出了一种新的运动学自标定方法。该方法基于冗余传感器测出的动平台全部位姿信息,利用运动学反解公式,建立了标定数学模型,并应用遗传算法进行参数辨识,避免了大量的偏导计算。标定后机床X轴定位精度由标定前的±0.06 mm提高到±0.03 mm,Y轴定位精度由标定前的±0.43mm提高到±0.07 mm,Z轴定位精度由标定前的±0.94 mm提高到±0.07 mm。该方法为改善并联机床的运动精度提供了一种有效手段,并为并联机床的闭环控制奠定了基础。To improve the motion precision of Parallel Machine Tools （PMT）, a novel self-calibration method was presented based on an original 5-Degree of Freedom （DOF） PMT. A model was achieved by using the inverse kinetic solution and all the information of the moving platform pose, which was measured by the redundant sensors. The genetic algorithm was applied to identify the parameters of the model and the massive calculation of the partial derivative was avoided. After calibration, the positional accuracy of PMT was remarkably improved. The precision of axis X was improved from ±0.06 mm to ±0.03 mm, Y from ±0.43 mm to ±0.07 mm and Z from ±0.94 mm to ± 0.07 mm. This method was an effective tool to improve the accuracy of PMT and achieve the closed loop control.

关 键 词：并联机床 5自由度 自标定 遗传算法 

分 类 号：TP242.3[自动化与计算机技术—检测技术与自动化装置]