Nonlinear Fault Diagnosis of Jet Engines by Using a Multiple Model-Based Approach

In this paper, a nonlinear fault detection and isolation (FDI) scheme that is based on the concept of multiple model (MM) approach is proposed for jet engines. A modular and a hierarchical architecture is proposed which enables the detection and isolation of both single as well as concurrent permanent faults in the engine. A set of nonlinear models of the jet engine in which compressor and turbine maps are used for performance calculations corresponding to various operating modes of the engine (namely, healthy and different fault modes) is obtained. Using the multiple model approach the probabilities corresponding to the engine modes of operation are first generated. The current operating mode of the system is then detected based on evaluating the maximum probability criteria. The performance of our proposed multiple model FDI scheme is evaluated by implementing both the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). Simulation results presented demonstrate the effectiveness of our proposed multiple model FDI algorithm for both structural and actuator faults in the jet engine.