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Kinematical calibration of a hybrid machine tool with Regularization method
Authors:Peng Huang  Jinsong Wang
Affiliation:a Institute of Manufacturing Engineering, Department of Precision Instruments and Mechanology, Tsinghua University, Beijing 100084, PR China
b University of Electronic Science and Technology, Chengdu 610054, PR China
c National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, PR China
Abstract:The hybrid machine tools, combining the advantages of serial and parallel type machine tools, provide more and more application opportunities for less-freedom parallel mechanism. Accuracy performance is still an important index of hybrid machine tool for industry application. In this study, configuration of a 3-P(4R)S-XY hybrid machine tool is first introduced. The 3-P(4R)S parallel mechanism can be simplified to a 3-PRS mechanism on kinematical calibration. Based on that, error model and error kinematics are derived to introduce all possible manufacturing and assembling errors into calibration. Then, identification matrix is derived by differentiating kinematical equations. Combining the advantages of calibration schemes based on both inverse and forward kinematics model, a new measurement scheme is put forward, in which not all freedoms of motions needs to be measured and error identification could be efficiently accomplished in one time measurement. In order to solve the ill-posed problem in error identification, practical Regularization methods are adopted. Finally, the kinematical calibration experiment of the prototype machine tool is performed with a combined measuring tool. The results of RTCP accuracy test reveal that the positioning accuracy is less than 0.05 mm in the 30° cone workspace. Calibration experiments for the prototype verify feasibility and effectivity of the more precise kinematical error model, the low-cost measurement scheme, and the error identification solution with Regularization method.
Keywords:Parallel mechanism  Error identification  Kinematical calibration  Regularization method
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