Applied Sciences (Mar 2023)

Structural Design of Aerostatic Bearing Based on Multi-Objective Particle Swarm Optimization Algorithm

  • Biqing Ye,
  • Guixin Yu,
  • Yidong Zhang,
  • Gang Li

DOI
https://doi.org/10.3390/app13053355
Journal volume & issue
Vol. 13, no. 5
p. 3355

Abstract

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Aerostatic bearings are considered crucial components that can improve the measurement accuracy of ground simulation tests of space equipment. A structural optimization design method is proposed to enhance the static performance of aerostatic bearings. A mathematical model which can quickly calculate the aerostatic bearing capacity and gas consumption is established, and the influence of structural parameters on bearing performance is analyzed using simulation software. By comparing the convergence time and convergence results of the algorithm using different initialization methods, the Latin hypercube initialization method is selected instead of the random initialization method. The multi-objective particle swarm optimization algorithm is used to obtain the optimal solution set distributed in the objective space. It is found that the optimized structural parameters meet the requirements of improving the capacity and reducing gas consumption, which verifies the method’s effectiveness in designing the structural parameters of aerostatic bearings.

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