Prediction and compensation of geometric error for translational axes in multi-axis machine tools

ORIGINAL ARTICLE
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Abstract

This paper proposes an integrated geometric error prediction and compensation method to eliminate the positioning inaccuracy of tool ball for a double ball bar (DBB) caused by the translational axes’ geometric errors in a multi-axis machine tool (MAMT). Firstly, based on homogeneous transform matrix (HTM) and multi-body system (MBS) theory, the positioning error model only considering the translational axes of a MAMT is established. Then, an integrated error parameter identification method (IEPIM) by using a laser interferometer is proposed. Meanwhile, the identification discrete results of geometric error parameters for the translational axes are obtained by identification experiments. According to the discrete values, the optimal polynomials of 18 position-dependent geometric errors (PDGEs) are founded. As a basis, an iterative compensation method is constructed to modify the NC codes generated with the ordinary compensation method in self-developed compensation software. Finally, simulation verification is conducted with these two compensation methods. Simulation results show the positioning errors for test path of tool ball calculated with the iterative compensation method that are limited within 0.001 mm, and its average accuracy and accuracy stability are improved by 79.5 and 52.2%, respectively. In order to further verify the feasibility of the presented method, a measuring experiment is carried out in XY plane of a five-axis machine tool by using DBB. The experiment results show that the maximum circularity error with the iterative compensation method is reduced about 40.4% than that with the ordinary compensation method. It is therefore reasonable to conclude that the proposed method in this paper can avoid the influence of the translational axes’ geometric errors on rotary ones during a DBB test.

Keywords

Translational axes Geometric error Positioning error Integrated error parameter identification method Iterative compensation method The optimal polynomials 

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2017

Authors and Affiliations

  1. 1.College of Mechanical Engineering & Applied Electronics TechnologyBeijing University of TechnologyBeijingPeople’s Republic of China
  2. 2.School of Mechanical and Electrical EngineeringZhengzhou University of Light IndustryZhengzhouPeople’s Republic of China

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