基于动态RBF网络的发动机起动过程模型辨识

A Dynamic Identification Model of Aeroengine Starting Process Based on the RBF Network

针对航空发动机在起动过程中各截面气流处于亚临界状态 ,难以利用传统的气动热力学方法进行建模的问题 ,本文利用发动机地面试验数据作为学习样本 ,采用动态径向基 (RBF)神经网络的方法 ,建立了航空发动机起动过程动态模型。仿真结果表明 ,利用该方法建立的发动机模型具有动态性好 ,精度高的优点 。

In the process of engine start,the airflow of every section is in subcritical condition.It's hard to construct a model with traditional thermodynamics methods.A dynamic identification model is set up in this paper based on Radial Basis Function network using ground test data as learning samples.The simulation results show the model has good dynamic performance and high accuracy,and opens a new way to building the model of engine at low speed.