基于双重卡尔曼滤波器的发动机故障诊断

Aeroengine fault diagnosis using dual Kalman filtering technique

提出了一种基于双重卡尔曼滤波器的航空发动机健康参数估计方法,实现了传感器发生故障情况下发动机故障的准确诊断.采用发动机动态工作点的测量数据,解决了可测量参数偏少导致故障诊断困难的问题;球面采样平方根UKF(Unscented Kalman filter)故障诊断滤波器具有更好的滤波稳定性与更低的计算量的要求,提高了故障诊断算法的效率与精度.某型双轴涡扇发动机故障诊断仿真结果表明,该方法可以准确的同步实现气路部件与传感器的故障诊断,是一种有效的航空发动机故障诊断方法.

A dual Kalman filter based health parameters estimation technique was proposed to conduct fault diagnosis of aeroengine components and sensors. Unsteady engine operation measurements were used to solve the diagnosis problem caused by limited amount of available sensors. Thereduced sigma point square root unscented Kalman filter （UKF） algorithm could improve the filtering stability and decrease the computational cost greatly. A fault diagnostic simulation was carried out for two-spool turbofan engine components and sensors, showing that the dual Kalman filtering algorithm is an effective aeroengine diagnostic technique.