Aircraft Engine Sensor Fault Diagnostics Based on Estimation of Engine's Health Degradation

Abstract

A duty in development of an on-line fault detection algorithm is to make it associate with estimation of engine's health degradation. For this purpose, an on-line diagnostic algorithm is put forward. Using a tracking filter to estimate the engine's health condition over its lifetime, can be reconstructed an onboard model, which is then made to match a real aircraft gas turbine engine. Finally, a bank of Kalman filters is applied in fault detection and isolation (FDI) of sensors for the engine. Through the bank, the real faults that have occurred can be detected and isolated. The on-line fault detection algorithm has the ability of maintaining the effectiveness over the engine's lifetime and is verified by simulation using a nonlinear engine model.