Research on the Optimal Design Approach of the Surface Texture for Journal Bearings

Abstract

Aiming to improve the comprehensive performance of the journal bearing system, this paper presents a multi-objective adaptive scale texture optimization design approach. A mixed lubrication model for the textured journal bearing system is established by considering the effects of cavitation and roughness. The geometrical parameters of the textures were co-optimized using a multi-objective grey wolf optimizer to obtain the optimal texture schemes that are suitable for different operating conditions. Through this approach, the influences of different texture schemes under transient operating conditions can be investigated. According to the results, it was found that different texture schemes result in different friction reduction effects. Proper surface texture is beneficial in increasing the minimum oil film thickness and reducing the possibility of asperity contact. The adaptive scale texture exhibits strong adaptability and achieves significant hydrodynamic effects. Therefore, the developed approach provides valuable insights for the optimization design of journal bearing systems.