Fault Detection and Isolation in Aircraft Systems Using Stochastic Nonlinear Modelling of Flight Data Dependencies

Abstract

This paper introduces a fault detection and isolation (FDI) scheme for aircraft systems based on the modelling of the relationships among flight variables. The modelling is performed by means of pooled nonlinear autoregressive with exogenous (NARX) excitation representations. During the system's operation in healthy mode, these relationships are valid. Hence, a scheme using statistical hypothesis testing is designed to detect changes in these relationships as a result of fault occurrence. The FDI scheme's performance and robustness are assessed with flights conducted under various external flight conditions (turbulence)