Abstract
In this paper, based on the multiple-model (MM) approach, a sensor fault diagnosis strategy is proposed for aero engines. The aeroengine corresponding Kalman filter bank was designed. The hypothesis test algorithm is used to find the probability of each mode, and then the sensor fault is detected and isolated based on the criterion of maximum probability. In addition, for multi-sensor fault diagnosis and estimation, a hierarchical architecture approach is used to achieve, thereby reducing the number of models and increasing the speed of calculation. In the simulation environment, the proposed multi-model method was used to study the fault diagnosis and estimation of a certain turbofan engine sensor. Simulation results show that the proposed multi-model method can effectively achieve sensor fault diagnosis and has good robustness.
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