基于进化算法的液体动力润滑轴承优化设计

Optimization Design of Liquid Dynamical Lubricated Bearing Based on Evolvement Algorithms

采用Matlab语言,分别运用改进型粒子群算法和基本粒子群算法,在最大限度满足液体动力润滑径向滑动轴承的承载量系数值,以达到滑动轴承承载能力的条件下,对内燃机径向滑动轴承进行了优化设计,计算机仿真结果表明:采用改进型粒子群算法优化的轴承孔直径、轴径直径、轴承宽度、承载量系数等优化参数效果最好,符合实际工艺要求,且滑动轴承承载能力最强。改进型粒子群算法优化结果明显优于基本粒子群算法的优化结果,从而表明了改进型粒子群算法应用于内燃机问题的优化求解切实可行。

Based on particle swarm algorithms, improved particle swarm algorithms and Matlab, optimization simulations regarding radial bearing in internal combustion engine were made in order to satisfy themaximum coefficient of carrying capacity and reach the bearing load capacity. The simulation results show that the improved particle swarm algorithms are the best in optimized simulation parameters including diameters, shaft diameters and width, and can meet the requirements of practical production technology. It also indicates that the improved particle swarm algorithms are practical in optimization of internal combustion engines.