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考虑到参数不确定性对转子径向变形的影响,提出了1种基于分布式协同响应面的涡轮转子径向变形稳健性优化方法。首先,利用Kriging模型建立各部件参数与径向变形响应面子模型,然后利用分布式协同响应面方法建立全局参数与转子径向变形的系统响应面模型。其次,利用系统响应面模型建立涡轮转子径向变形稳健性优化模型,并采用果蝇优化算法来进行稳健性优化求解。优化后涡轮转子径向变形的均值以及标准差比优化前分别降低了7.3%和4.97%,计算结果表明:该方法在工程应用中的可行性和有效性。
Considering the influence of parameter uncertainty on rotor radial deformation, a robust optimization method for rotor radial deformation based on distributed cooperative response surface is proposed. Firstly, Kriging model is used to establish the parameters of each component and the radial deformation response surface sub-model, and then the distributed response surface method is used to establish the system response surface model of global parameters and rotor radial deformation. Secondly, the system response surface model is used to establish the optimization model of rotor rotor radial deformation robustness, and the fruit fly optimization algorithm is used to optimize the robustness. The mean value and standard deviation ratio of the optimized radial turbine rotor are reduced by 7.3% and 4.97% respectively before optimization. The calculation results show that this method is feasible and effective in engineering application.