Abstract: A simulation model of oil film of hollow shaft hydrostatic bearing is established. Simulations are carried out to analyze the effects of the oil cavity angle, deflection angle and oil cavity width on the bearing capacity and hydraulic power consumption of the hydrostatic bearing. The bearing capacity and hydraulic power consumption of a large-scale ball mill with motor power of 8000 kW are taken as the optimization objects. The constraint conditions are the minimum load provided by the hydrostatic bearing and the allowable stress of the bearing bush. A multi-objective optimization design method of the hydrostatic bearing is proposed based on the radial basis function(RBF) surrogate model and the multi-objective Particle Swarm Optimization (PSO) algorithm. The Pareto optimal solution set is obtained, and the optimal compromise solution is selected using TOPSIS method based on grey relational degree. Optimization results show that the optimized capacity of the hydrostatic bearing is increased by 2.99%, the hydraulic power consumption is reduced by 3.87%, and the weight of the working medium in the shell of the ball mill is reduced by 8.74%.

Key words: mechanical design, hollow shaft hydrostatic bearing, surrogate model, multi-objective optimization, technique for order preference by similarity to an ideal solution(TOPSIS), particle swarm optimization(PSO) algorithm