基于Isight的壓氣機(jī)三維葉片魯棒性優(yōu)化

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摘 要：以Isight軟件為基礎(chǔ)，搭建葉片魯棒性優(yōu)化平臺(tái)，基于構(gòu)建的RBF神經(jīng)網(wǎng)絡(luò)模型和蒙特卡羅方法對(duì)壓氣機(jī)Rotor37進(jìn)行魯棒性優(yōu)化。優(yōu)化結(jié)果表明：壓氣機(jī)性能曲線整體向左上方移動(dòng)，裕度幾乎不變，選取的兩個(gè)優(yōu)化工況處效率的均值分別提高了0.24%和0.46%，方差分別降低了16.3%和15%。

關(guān)鍵詞：壓氣機(jī)；葉片；魯棒性優(yōu)化；RBF神經(jīng)網(wǎng)絡(luò)；蒙特卡羅方法；效率；裕度

中圖分類號(hào)：TH138.5  文獻(xiàn)標(biāo)志碼：B  文章編號(hào)：1671-5276（2024）05-0126-04

Robustness Optimization of Compressor Three-dimensional Blades Based on Isight

Abstract：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.

Keywords：compressor；blade；robustness optimization；RBF neural network；Monte Carlo method；efficiency；margin

0 引言

葉片是組成航空發(fā)動(dòng)機(jī)的重要部件，但在加工過程中會(huì)不可避免地出現(xiàn)加工誤差。（剩余4719字）