基于双模型自适应估计的大气数据传感器故障诊断方法

Fault diagnosis method of air data sensor based on double-model adaptive estimation

大气湍流是大气中一种不规则的随机运动,在机载大气数据传感器的测量过程中,大气湍流影响与传感器故障相互耦合,导致大气数据传感器故障诊断算法无法将故障与湍流影响解耦。针对大气湍流影响下的大气数据传感器故障诊断问题,基于惯性测量单元和导航姿态解算,考虑湍流对大气系统的影响,建立新型大气系统模型及量测模型。在对双模型自适应估计算法进行扩展后,引入湍流对系统影响的协方差自适应更新方法,实现存在未知扰动情况下故障状态的无偏估计。仿真结果表明,该算法可以有效实现对固定偏差故障、漂移偏差故障和振荡故障的诊断。

Atmospheric turbulence is an irregular random motion in the atmosphere.During the measurement of airborne air data sensors,atmospheric turbulence effects and sensor faults are coupled with each other,leading to the inability of air data sensor fault diagnosis algorithms to decouple faults from turbulence effects.In view of the fault diagnosis problem of air data sensors under the effects of atmospheric turbulence,a new atmospheric system model and measurement model are developed based on inertial measurement units and navigation attitude solving,considering the effects of turbulence on the atmospheric system.After extending the double-model adaptive estimation algorithm,the covariance adaptive update of the effect of turbulence on the system is introduced to achieve an unbiased estimation of the fault state in the presence of unknown disturbances.Simulation results show that the algorithm can effectively achieve diagnosis of fixed deviation faults,drift deviation faults,and oscillation faults.