摘要
给出了基于改进粒子群算法的圆锥滚子轴承优化设计方法。该算法通过对每一次进化计算后记忆中的最优粒子进行随机摄动操作来提高解的精度和算法的搜索效率,同时对种群中的最差粒子重新进行初始化来保持种群的多样性以避免陷入局部最优解;并采用惩罚函数法来处理约束,取得了较好的效果。计算实例表明该方法高效可行,优化结果可直接作为工程设计的参考。
A way of optimal design is proposed for tapered roller beatings based on improved particle swarm optimization. To retain diversity of population and avoid being plunged to local optimum, it initializes the worst individual in population over again, and the best previous particle of each individual is randomly perturbed after evolutionary computation every time to improve its running efficiency and precision of over all optimization searching. At the same time, the penalty function methods are used to process the constraints. Actual calculation shows that the method is feasible and efficient and the optimal results can be served as reference to engineering design.
出处
《轴承》
北大核心
2009年第9期4-7,共4页
Bearing
关键词
圆锥滚子轴承
粒子群算法
优化设计
tapered roller bearing
particle swarm optimization
optimal design
