Sensor Soft Failure Diagnostics Based on Aero-Engine On-Board Adaptive Model

It is well known that the physical engine components deteriorate gradually due to wear and tear on blades and the casing as an engine operates over time. In this paper, a steady-state model, which takes the component performance deteriorations into account, is developed. The deterioration can be tracked by one Kalman filter. Then the on-board model could be re-constructer based on the estimated values of Kalman filter. After all of this, the on-board model can match with the actual engine. At last a bank of Kalman filters is applied in fault detection and isolation (FDI) of sensors for aircraft gas turbine engine. The engine output values and Kalman filter estimated were used to fault detection and isolation. The proposed approach is applied to a nonlinear engine in this paper, the simulation results indicate that the proposed FDI system is promising for reliable diagnostics of aircraft engines.