运载火箭伺服机构故障检测与诊断的扩展多模型自适应方法

Extended multiple model adaptive method for fault detection and diagnosis of launch vehicle's servo mechanism

针对运载火箭伺服机构故障,提出一种基于扩展多模型自适应估计的故障检测与诊断算法。建立考虑伺服机构故障的运载火箭姿态动力学模型;将故障角度作为状态变量得到增广状态空间模型;利用扩展卡尔曼滤波器进行状态向量和故障参数的非线性估计,并基于传感器测量数据采用假设检验算法在线计算故障发生的概率;给出基于扩展多模型自适应估计的故障检测与诊断算法流程。仿真结果表明,该方法在无故障时可对伺服机构进行健康监测;在单台伺服机构故障下,可以及时准确判断出哪一台芯级伺服机构发生故障,并可准确估计出伺服机构故障下的发动机摆角角度。

Aiming at the servo mechanism fault of launch vehicle,a FDD(fault detection and diagnosis)based on extended multiple model adaptive estimation was proposed.Attitude dynamic model of launch vehicle considering servo mechanism fault was established;the fault angle was used as the state variable to obtain the augmented state space model;the nonlinear estimation of state vectors and fault parameters was carried out by using the extended Kalman filter,and based on the sensor measurement data,the occurrence probability of faults was calculated by the hypothesis testing algorithm;the fault detection and diagnosis procedure based on the extended multiple model adaptive estimation was presented.Simulation results shows that,not only the health monitoring of the servo mechanism can be carried out by the algorithm without fault,but also under single servo mechanism fault,the core servo mechanism whose fault appeared can be timely and exactly detected through the algorithm,and the angle of nozzle under servo mechanism fault can be estimated accurately.