Multi-objective optimization of the oil cavity structure of constant flow hydrostatic thrust bearing
YAN Zhongjie
LI Yunpeng
WEI Wei
DU Xiaotong
YANG Yanshuai
MI Zhentao
Abstract：[Objective]Aiming at the multi-dimensional and nonlinear characteristics of oil cavity structure optimization for constant flow hydrostatic thrust bearings,multi-objective optimization research on the oil cavity structure was carried out to realize the collaborative optimization of improving oil film stiffness,load-carrying overturning moment and reducing temperature rise,and provide reference for the structural design of hydrostatic bearings.[Methods]Firstly,a multi-objective optimization mathematical model of the oil cavity structure was established by taking the multi-pad constant flow hydrostatic bidirectional thrust bearing as the research object and selecting oil film stiffness,maximum load-carrying overturning moment and temperature rise as the objective functions.Secondly,the inertia weight and learning factor of the multi-objective particle swarm optimization algorithm were improved,and the balance between the global and local search capabilities of the algorithm was realized through cosine decreasing strategy and nonlinear adjustment to complete the optimal design of the structural parameters of the bearing oil cavity.Thirdly,a simplified model of the single oil cavity of the bearing was established in SolidWorks software,and a high-quality structured grid was manually divided in ICEM software to construct a finite element model of the flow field.Finally,the steady-state simulation analysis of the oil cavity flow field was carried out by Fluent software to compare and verify the improvement effect of the bearing load capacity after optimization.[Results]After optimization by the improved algorithm,the oil film stiffness of the bearing is increased by 22.5%,the theoretical calculated value of the maximum load capacity is increased by 11.9%,the maximum load-carrying overturning moment is increased by 21.2%,and the temperature rise is reduced by 2.13%.The flow field simulation results show that the maximum load capacity of the bearing is increased by 12.8%,which is highly consistent with the theoretical calculated value,which verifies the feasibility of the improved multi-objective particle swarm optimization algorithm applied in the multi-objective optimization of the oil cavity structure of hydrostatic bearings.
Keywords：Hydrostatic bearingMulti-objective optimizationMulti-objective particle swarm optimization algorithmFlow simulation algorithmOil cavity structure
Publication Date：2026-05-31
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：8( 143-150 )