涡轮转子径向变形多目标协同稳健性优化

考虑到涡轮转子径向变形对涡轮叶尖径向间隙以及篦齿径向封严间隙的影响,提出涡轮转子径向变形多目标协同稳健性优化方法。利用基于Kriging模型的分布式协同响应面法(DCRSM)分别建立涡轮转子和涡轮篦齿的参数与径向变形间的响应面模型,并求解单目标下的稳健最优解。采用理想点法建立涡轮转子和篦齿径向变形多目标协同稳健性优化模型,并进行多目标协同稳健性优化求解。优化结果显示:提出的多目标协同稳健性优化方法与单目标稳健性优化方法相比涡轮转子和篦齿径向变形量的标准差分别降低了2.6%和4.9%。提出的方法为涡轮转子参数设定提供一定的参考。 

Multi-objective collaborative robust optimization for turbine rotor radial deformation

A Multi-objective robust collaborative optimization method for turbine rotor radial deformation was presented. The influence of turbine rotor radial deformation was considered for turbine blade tip clearance and labyrinth seal clearance. The approximation function model of parameters with rotor and labyrinth seal radial deformation was built by the Kriging method based distributed collaborative response surface method (DCRSM). The single objective robust optimization result was generated by using those response surface approximation models. The ideal point method was selected to construct the multi-objective robust collaborative optimization model of turbine rotor and labyrinth seal radial deformation. The multi-objective collaboration robust optimization process was implemented. Compared with the results of single objective optimization, the results of presented collaborative robust optimization showed that the turbine rotor and labyrinth radial deformation standard deviation decreased by 2.6% and 4.9%, respectively. The proposed method provides a reference for turbine rotor parameters design.