基于群智能算法的二级减速器中间轴公差优化

Tolerance Optimization of Intermediate Axle in Two-stage Reducer Based on Swarm Intelligence Algorithm

为了降低二级减速器中间轴的制造成本,提出了3种基于群智能算法的中间轴公差优化设计方法。构造了以制造成本与质量损失成本的和为最小目标函数及以加工能力、加工工艺要求为约束条件的数学模型。利用遗传算法、混合蛙跳算法和粒子群算法计算了中间轴各组成环的公差和封闭环公差。与其他群智能算法和传统的等公差法、等精度法相比,粒子群算法的收敛速度最快,效率最高。

In order to reduce the manufacturing cost of intermediate axle of secondary reducer,three optimization design methods of intermediate axle tolerance based on swarm intelligence algorithm are proposed.A mathematical model with the sum of manufacturing cost and quality loss cost as the minimum objective function and the constraints of processing capacity and process requirements is constructed.The tolerances of each ring of the intermediate axis and the closed ring are calculated by using genetic algorithm,hybrid frog leaping algorithm and particle swarm optimization algorithm.Compared with other swarm intelligence algorithm,traditional equal tolerance method and equal precision method,particle swarm optimization algorithm has the fastest convergence speed and the highest efficiency.