基于UIO的航空发动机执行机构故障诊断

为了提高航空发动机诊断过程中对噪声干扰和模型参数变化的鲁棒性,应用UIO(Unknown Input Ob-server)理论估计发动机动态系统的工作状态,通过干扰正交投影弱化外界干扰对状态估计的影响,处理了航空发动机执行机构的故障诊断问题。对航空发动机执行机构设计一组UIO观测器,其中每个UIO用于监测估计对应执行机构的故障偏移量,计算系统输出理论估计值与发动机实际测量信号间的残差数据,分析残差队列的幅值特性,实现航空发动机执行机构系统的故障检测和隔离。某型涡扇发动机上的实验结果表明,与Kalman滤波算法相比,UIO诊断方法更能鲁棒地检测和隔离出执行机构故障。

UIO-Based Diagnosis of Aeroengine Actuator Faults

In order to improve the robustness of aircraft engine diagnosis against noisy disturbances and parameter variation,this paper addresses the problem of diagnosing actuator fault in aeroengine control systems.The proposed approach applies the unknown input observer(UIO) theory to estimate operational states in an operating aeroengine.The effect of exogenous disturbances on state estimation is mitigated in an orthogonal-projection-of-disturbances manner.As for engine actuators,we designed a group of UIOs,each of which is used to monitor the amount of faulty offset in its corresponding actuator.A residual vector between the estimated values and the measured outputs is further evaluated.In addition,the characteristics in the magnitude of the residuals are analyzed to achieve the detection and isolation of faults in aeroengine actuators.Experimental results on some turbofan engine indicate that the UIO-based method can more robustly detect and isolate actuator faults in an aeroengine than the Kalman filter-based algorithm.