基于多目标优化模型的扇叶最优分组与排列方案

Optimal Grouping and Arrangement Scheme of Fan Blades Based on Multi-objective Optimization Model

衡量某种机械单片扇叶结构优劣的指标有“质量”与“转动频率”两种参数,为了合理地装配整个风扇,需要相邻组的扇叶质量差达到最小,同时相邻叶片的频率差达到最大。首先构建一个单目标优化的质量分组模型,其后引入递推型动态规划算法,使得相邻组的扇叶质量差达到最小。同时考虑转动频率的影响,再建立一个多目标优化的质量分组模型,采用动态权重线性加权法,通过对比不同权重下相邻扇叶组的最大质量差和相邻扇叶的最大频率差,发现当A目标和B目标的权重均为0.5时,该模型所给出的方案效果最佳。

The indicators for measuring the quality of a single fan blade structure of a certain machinery include two parameter:“mass”and“rotational frequency”,In order to assemble the entire fan reasonably,it is necessary to minimize the mass difference between adjacent groups of fan blades and maximize the frequency difference between adjacent blades.Firstly,a mass grouping model with single objective optimization is constructed,and then a recursive dynamic planning algorithm is introduced to minimize the mass difference between adjacent groups of fan blades.At the same time,considering the influence of rotational frequency,a mass grouping model with multi-objective optimization is established,and the dynamic weight linear weighting method is used,by comparing the maximum mass difference between adjacent groups of fan blades and maximum frequency difference between adjacent blades under different weights,it is found that when the weights of target A and target B are both 0.5,the scheme provided by the model has the best effect.