RESEARCH ARTICLE

Dynamic modeling of hydrostatic guideway considering compressibility and inertia effect

  • Yikang DU 1 ,
  • Kuanmin MAO , 1 ,
  • Yaming ZHU 1 ,
  • Fengyun WANG 1 ,
  • Xiaobo MAO 1 ,
  • Bin LI 1,2
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  • 1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
  • 2. State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China

Received date: 10 Jan 2015

Accepted date: 10 Feb 2015

Published date: 01 Apr 2015

Copyright

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg

Abstract

Hydrostatic guideways are used as an alternative to contact bearings due to high stiffness and high damping in heavy machine tools. To improve the dynamic characteristic of bearing structure, the dynamic modeling of the hydrostatic guidway should be accurately known. This paper presents a “mass-spring-Maxwell” model considering the effects of inertia, squeeze, compressibility and static bearing. To determine the dynamic model coefficients, numerical simulation of different cases between displacement and dynamic force of oil film are performed with fluent code. Simulation results show that hydrostatic guidway can be taken as a linear system when it is subjected to a small oscillation amplitude. Based on a dynamic model and numerical simulation, every dynamic model’s parameters are calculated by the Levenberg-Marquardt algorithm. Identification results show that “mass-spring-damper” model is the most appropriate dynamic model of the hydrostatic guidway. This paper provides a reference and preparation for the analysis of the dynamic model of the similar hydrostatic bearings.

Cite this article

Yikang DU , Kuanmin MAO , Yaming ZHU , Fengyun WANG , Xiaobo MAO , Bin LI . Dynamic modeling of hydrostatic guideway considering compressibility and inertia effect[J]. Frontiers of Mechanical Engineering, 2015 , 10(1) : 78 -88 . DOI: 10.1007/s11465-015-0331-4

Acknowledgements

This work was supported by the grants from Key Projects in the National Science and Technology Pillar Program (Grant No. 2012BAF08B01).
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