The invention relates to the field of hydrostatic bearings, in particular to a multi-objective optimization design method for a quantitative hydrostatic
thrust bearing, and provides the multi-objective optimization design method for the quantitative hydrostatic
thrust bearing aiming at the multi-dimensional and nonlinear characteristics of the structural
optimization problem of the hydrostatic bearing. According to the method, multiple targets of the hydrostatic bearing are optimized by applying a multi-target
particle swarm algorithm, and the problems of subjectivity and complexity of weight determination of a weighted summation method and the problem that an equivalent optimal solution cannot be found when a Pareto
leading edge is non-convex are avoided; improving parameters of the multi-target
particle swarm algorithm to improve the convergence speed of the
algorithm and prevent particles from falling into
local optimum; according to the method, on the basis of a deduced theoretical
mathematical model of the hydrostatic bearing, an optimization model is established with the axial
oil film rigidity, the overturning
bearing capacity and the temperature rise performance as objective functions,
MATLAB software is used for designing and applying an improved multi-objective
particle swarm optimization algorithm for structural parameter optimization, the theoretical rigidity of the bearing is improved by 78.75%, and the theoretical overturning
bearing capacity is improved by 37.17%; model division grids are established according to parameters before and after optimization,
fluid simulation is carried out, oil
cavity pressure distribution is obtained, the bearing rigidity is calculated, it is verified through
simulation comparison that the bearing rigidity is improved by 73.81%, and the method is beneficial to improving the design efficiency and the bearing performance of the hydrostatic bearing.