The optimization design for the journal-thrust couple bearing surface texture based on particle swarm algorithm

Journal-thrust coupled bearings (JTC bearings), unlike conventional journal or thrust bearings, require consideration of both reducing friction coefficient in the journal part while increasing the load-carrying capacity in the thrust part during lubrication design. This study established a thermal-elastohydrodynamic mixed lubrication model for JTC bearings considering flow, pressure, and thermal continuity conditions, validated through experiments. Based on this, the influence of texture parameters on lubrication under real heavy load conditions was preliminarily investigated. The orthogonal test design was then used to determine the texture parameter that had the greatest impact on optimization. Subsequently, particle swarm optimization (PSO) algorithm was employed for synchronous optimization design of textures for both journal and thrust parts.