航空发动机健康参数的卡尔曼滤波估计方法分析

Kalman Filter for Aero-Engine Health Parameter Estimation Analysis

针对航空发动机气路部件健康参数估计问题,研究了基于线性和非线性模型的卡尔曼滤波估计方法。通过对气路部件渐变故障的仿真,比较了卡尔曼滤波(KF)、扩展卡尔曼滤波(EKF)、无味卡尔曼滤波(UKF)三种方法对健康参数的估计效果,对EKF在常增益条件下的仿真用时与估计结果进行了研究。结果表明,EKF可根据需要求取卡尔曼增益,能在较少计算量下得到较好的估计结果,是一种实用的非线性参数估计方法。

For health parameters estimation of aero-engine gas path components, we studied Kalman filter estimation methods which based on linear and nonlinear Kalman filter （KF）. Through simulation of gradual faults of gas path components, the estimation results of KF, extended Kalman filter （EKF）, and unscented Kalman filter （UKF） were compared. The simulation time and estimation results of EKF on the condition of constant gain were studied. Results show that EKF can obtain Kalman gain according to demand and get better estimation results with lower cost. EKF is a practical nonlinear parameter estimation method.