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Author:

Niu, Peng (Niu, Peng.) | Cheng, Qiang (Cheng, Qiang.) | Chen, Kui (Chen, Kui.) | Yang, Congbin (Yang, Congbin.)

Indexed by:

EI Scopus

Abstract:

At the design stage of a machine tool, how to accurately predict and analyze the motion error of linear axis system is a difficult problem for designers. This research is of great significance to optimize the initial design scheme of the machine tool and improve the geometric accuracy. A kinematic errors prediction and accuracy improvement method of guide rail based on assembly and manufacturing analysis was proposed. Firstly, the distribution law of bolt preload under a specific assembly sequence was revealed by finite element analysis (FEA). Based on a probability analysis of assembly parameters, the statically indeterminate mechanical model of guide rail assembly deformation was established. Secondly, a Fourier function with tolerance as amplitude was established to characterize the surface topography of the guide rail installation base surface satisfying Dirichlet boundary conditions. Based on the influence of manufacturing and assembly, the final profile curve function of the guide rail is obtained, and the straightness and angular kinematics error (SAEs) are accurately predicted. The prediction accuracy of the straightness error is 98.5%. Referring to the prediction results, the targeted accuracy improvement measures for the linear axis platform are proposed. The straightness kinematics error of the guide rail is reduced from 9.11um to 4.28um. The proposed method can accurately predict the motion error of the guide rail and guide the precision improvement of the linear axis. © 2023 SPIE.

Keyword:

Friction Boundary conditions Forecasting Topography Kinematics Errors Machine tools

Author Community:

  • [ 1 ] [Niu, Peng]Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Niu, Peng]Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Cheng, Qiang]Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Cheng, Qiang]Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Chen, Kui]Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 6 ] [Chen, Kui]Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 7 ] [Yang, Congbin]Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 8 ] [Yang, Congbin]Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing; 100124, China

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Source :

ISSN: 0277-786X

Year: 2023

Volume: 12801

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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