針對實驗室不像飛機上可以通過復雜的機械傳動裝置確定發動機轉速控制系統的給定轉速，在研究分析了某渦扇發動機給定轉速影響因素的基礎上，提出了一種確定該型發動機給定轉速的徑向基函數（RBF）神經網絡算法，并以試驗數據為訓練樣本，建立了確定發動機給定轉速的RBF 神經網絡模型。通過試驗驗證，結果表明該方法具有學習速度快、計算精度高等特點，將其應用于確定航空發動機的給定轉速是行之有效的。
關鍵詞：RBF 神經網絡，航空發動機，給定轉速，燃油泵調節器
Abstract: Because aero-engine theoretic speed can be known not through setting up mechanical gearing, after analyzing the factors of affecting some turbofan engine theoretic speed , we present a RBF network arithmetic that can makes certain of aero-engine theoretic speed. We set up the RBF network model that can make certain of aero-engine theoretic speed by using experimental data as the network’s learning stylebook. Through experiment,
the result shows that the method has the advantage of faster learning rate, higher calculating precision, that it can be used to make certain of aero-engine theoretic speed.
Keywords: RBF NN, aero-engine, theoretic speed, oil-pump adjustor.