多工况条件下滚针轴承的改进粒子群优化方法

Optimal Design of Needle Roller Bearings under Multi-conditions Based on Improved Particle Swarm Optimization

为了获得在复杂工况下滚针轴承的最优尺寸参数,提出了一种利用改进粒子群算法优化滚针轴承尺寸参数的方法.在考虑了污染、载荷、润滑、转速、游隙、倾斜、滚针修形等工况的前提下,建立了以滚针轴承额定修正寿命为目标函数的有约束优化模型;采用随机权重策略改进惯性权重值,以反余弦策略来调整学习因子大小,用保证粒子合法性的方法求解约束的问题,从而实现了多工况下滚针轴承非线性优化设计;最后通过对优化结果进行对比分析,验证了该方法是一种有效的轴承设计方法.

Based on improved particle swarm optimization （IPSO）, an optimal method is proposed for needle roller bearings design so that the optimal dimensional parameters can be obtained when the bearings operates under complex conditions. By taking the operational conditions such as pollution, load, lubrication, speed, clearance, tilt and needle shape into account, a constraint optimal model is established which takes the modified rating life of needle roller bearings as the objective function. The random weighting strategy and the arccosine strategy are used to improve the inertia weight and adjust the learning factor, respectively. The constraints are solved by using the method of ensure particle legitimacy. As a result, the nonlinear optimization design of needle roller bearings was realized by IPSO. By analyzing the optimization results, the proposed method shows its effectiveness for needle roller bearings design.