基于多模型的舵面故障诊断方法研究

Research on multi-model based fault diagnosis method of control surface

为了有效识别舵面破损带来的舵效减弱等问题,以IFSTA变稳飞机的非线性模型为基础,建立了合适的舵面故障模型库;利用卡尔曼滤波算法计算各故障模型的预测误差,使用多元高斯分布的概率密度公式计算各模型估计误差的概率密度;最终通过各模型的预测概率实现飞机舵面故障识别。仿真及试验表明,所提方法能够快速地将当前故障与故障库中的模型进行匹配,具有良好的故障诊断能力。

In order to effectively identify the problem such as the rudder effectiveness weakening caused by rudder surface damage,a suitable fault model library of control surface is established based on the nonlinear model of IFSTA variable stability aircraft.A Kalman filter algorithm is used to calculate the prediction error of each fault model,and the probability density of estimation error is calculated with the probability density formula of multivariate Gaussian distribution.Finally,the fault diagnosis of control surface is realized by the prediction probability of each model.Simulation and test results show that the method can quickly match the current fault with the model in the fault model library,and has good fault diagnosis capability.