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出 处:《系统仿真学报》2008年第21期5840-5842,5847,共4页Journal of System Simulation
摘 要:在飞机舵面故障诊断系统中,及时准确的故障预报对提高飞机的安全性具有极其重要的意义,针对飞机舵面故障预报系统的设计要求,建立了神经网络故障预测模型以及训练算法,该预测模型采用三层BP网络模型,还对神经网络的预测精度给出了评价函数。最后,为了验证所述方法的有效性,结合风洞实验数据,对某机舵面故障模式之一的方向舵卡死进行了预测和分析,并与传统的ARMA方法进行了比较,结果充分表明了该神经网络预测模型的有效性和优越性。In the airplane steering surface fault diagnosis system, timely and accurate forecast of failure is of great significance to improve the safety of the airplane. According to the design requirements of the airplane steering surface fault forecast system, the neural network fault forecast model and training algorithm were established. The three-tier model BP network model was applied in the fault forecast model. The evaluation function of the forecast accuracy was proposed. Finally, in order to validate the effectiveness of the method described, combining with the wind tunnel test data, forecast and analysis upon a kind of airplane steering surface failure mode of rudder block were done. Compared to the traditional method of ARMA, the result shows that the neural network model is of effectiveness and superiority.
分 类 号:TP206.3[自动化与计算机技术—检测技术与自动化装置]
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