Abstract
This paper proposed a method to update the on-line health reference baseline of the On-Board Engine Model (OBEM) to maintain the effectiveness of an in-flight aircraft sensor Fault Detection and Isolation (FDI) system, in which a Hybrid Kalman Filter (HKF) was incorporated. Generated from a rapid in-flight engine degradation, a large health condition mismatch between the engine and the OBEM can corrupt the performance of the FDI. Therefore, it is necessary to update the OBEM online when a rapid degradation occurs, but the FDI system will lose estimation accuracy if the estimation and update are running simultaneously. To solve this problem, the health reference baseline for a nonlinear OBEM was updated using the proposed channel controller method. Simulations based on the turbojet engine Linear-Parameter Varying (LPV) model demonstrated the effectiveness of the proposed FDI system in the presence of substantial degradation, and the channel controller can ensure that the update process finishes without interference from a single sensor fault.
Highlights
RESEARCH ARTICLEOPEN ACCESS Citation: Liu X, Xue N, Yuan Y (2017) Aircraft engine sensor fault diagnostics using an on-line OnBoard Engine Model (OBEM) update method
Because fault diagnostics are crucial for flight safety[1], several effective sensor Fault Detection and Isolation (FDI) approaches have been developed recently[2, 3], such as fault detection observer in Takagi–Sugeno’s form, a bank of neural networks and so on
To update the OnBoard Engine Model (OBEM) on-line, this paper proposes a new method that can be free from sensor fault and accommodate rapid degradation
Summary
OPEN ACCESS Citation: Liu X, Xue N, Yuan Y (2017) Aircraft engine sensor fault diagnostics using an on-line OBEM update method. This paper proposed a method to update the on-line health reference baseline of the OnBoard Engine Model (OBEM) to maintain the effectiveness of an in-flight aircraft sensor Fault Detection and Isolation (FDI) system, in which a Hybrid Kalman Filter (HKF) was incorporated. It is necessary to update the OBEM online when a rapid degradation occurs, but the FDI system will lose estimation accuracy if the estimation and update are running simultaneously. To solve this problem, the health reference baseline for a nonlinear OBEM was updated using the proposed channel controller method. Simulations based on the turbojet engine Linear-Parameter Varying (LPV) model demonstrated the effectiveness of the proposed FDI system in the presence of substantial degradation, and the channel controller can ensure that the update process finishes without interference from a single sensor fault
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