According to the requirement of prognostics and health management system in turbofan engine, a prognostics approach based on components health parameter estimation is presented for the gas path faults. The health evaluation is used to anticipate future maintenance and prognoses the gas path fault. The application considered is turbofan engine health parameter estimation, which offers the benefits of improving safety and reducing operating costs. The emphasis is focused on the research of applying Kalman filter to estimate engine component efficiencies and flow capacities, which are referred to as health parameters. The health parameters that tried to estimate can be modeled as slowly varying biases. The state vector of the dynamic model is augmented to include the health parameters, which are estimated with a Kalman filter. On the basis of engine state and the varying rate of the health parameters, the gas path faults can be prognosticated. Finally the example for the deteriorated engine is established in H = 15 km, Ma = 1.6. Simulation results from application to a turbofan model show that the system has perfect performance of estimating the health parameter. The simulation results demonstrate the effectiveness of this method, particularly for turbofan engine health estimation.%为了满足新一代航空发动机对故障预测与健康管理系统的需求,针对气路故障预测问题,以某型双转子、双涵道涡轮风扇发动机为对象,研究了把性能健康参数作为状态量扩展至状态方程,利用卡尔曼滤波器对状态变量进行估计,以估计出健康参数;并以该健康参数为基础,预测发动机的气路故障;最后以某涡扇发动机数学模型作为仿真对象,以H=15 km、Ma=1.6为仿真设计点,利用该工作点的线性状态方程设计了扩展卡尔曼滤波器,对健康参数进行了估计.仿真结果表明,状态估计器能够快速、较为准确地估计发动机的性能退化系数,从而能够较为准确地预测故障发生的时间,为航空装备的保障提供理论依据.
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