基于Isight的压气机三维叶片鲁棒性优化  

Robustness Optimization of Compressor Three-dimensional Blades Based on Isight

作　　者：龚志豪 杨荣菲[1] GONG Zhihao;YANG Rongfei(College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)

机构地区：[1]南京航空航天大学能源与动力学院,江苏南京210016

出　　处：《机械制造与自动化》2024年第5期126-129,共4页Machine Building & Automation

摘　　要：以Isight软件为基础,搭建叶片鲁棒性优化平台,基于构建的RBF神经网络模型和蒙特卡罗方法对压气机Rotor37进行鲁棒性优化。优化结果表明:压气机性能曲线整体向左上方移动,裕度几乎不变,选取的两个优化工况处效率的均值分别提高了0.24%和0.46%,方差分别降低了16.3%和15%。A blade robustness optimization platform was built based on Isight software,and with the constructed RBF neural network model and by Monte Carlo method,the robustness optimization of Rotor37 was carried out.The optimization results show that the overall performance curve moves to the left and up with nearly no change of margin,the average efficiency increases by 0.24%and 0.46%,and the variance decreases by 16.3%and 15%respectively at the two selected optimization conditions.

关 键 词：压气机 叶片 鲁棒性优化 RBF神经网络 蒙特卡罗方法 效率 裕度 

分 类 号：TH138.5[机械工程—机械制造及自动化]