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[期刊论文]

Geometric error modeling and source error identification methodology for a serial-parallel hybrid kinematic machining unit with five axis

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author:

Shen, Y. (Shen, Y..) [1] | Tang, T. (Tang, T..) [2] | Ye, W. (Ye, W..) [3] | Unfold

Indexed by:

Scopus

Abstract:

To meet the high-precision positioning requirements for hybrid machining units, this article presents a geometric error modeling and source error identification methodology for a serial-parallel hybrid kinematic machining unit (HKMU) with five axis. A minimal kinematic error modeling of the serial-parallel HKMU is established with screw-based method after elimination of redundant errors. A set of composite error indices is formulated to describe the terminal accuracy distribution characteristics in a quantitative manner. A modified projection method is proposed to determine the actual compensable and noncompensable source errors of the HKMU by identifying such transformable source errors. Based on this, the error compensation and comparison analysis are carried out on the exemplary HKMU to numerically verify the effectiveness of the proposed modified projection method. The geometric error evaluations reveal that the parallel module has a larger impacts on the terminal accuracy of the platform of the HKMU than the serial module. The error compensation results manifest that the modified projection method can find additional compensable source errors and significantly reduce the average and maximum values of geometric errors of the HKMU. Hence, the proposed methodology can be applied to improve the accuracy of kinematic calibration of the compensable source errors and can reduce the difficulty and workload of tolerance design for noncompensable source errors of such serial-parallel hybrid mechanism.  © The Author(s), 2024.

Keyword:

error compensation error identification error modeling geometric error hybrid kinematic machining unit source errors

Community:

  • [ 1 ] [Shen Y.]School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, China
  • [ 2 ] [Tang T.]School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, China
  • [ 3 ] [Tang T.]State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China
  • [ 4 ] [Ye W.]School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, China
  • [ 5 ] [Zhang J.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China

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Source :

Robotica

ISSN: 0263-5747

Year: 2024

1 . 9 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

30 Days PV: 0

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