A hybrid approach for aircraft fault diagnosis based on fault inference and fault identification

A cockpit instrumentation system provides various elements of information for pilots. However, logical inference based on a cockpit instruments fault tree (FT) and reliability sometimes cannot give a correct diagnosis of failures. In addition, in flight control systems (FCS), a fault identification method based on the multiple-model (MM) estimator cannot find the basic fault cause. To deal with these problems, a hybrid approach which is capable of integrating inference and fault identification is proposed. In this approach, the event nodes of the FT which have correlations to the FCS are separated into modules. Each module corresponds to a fault mode of the FCS. To use these correlations, fault inference and the MM estimator can share fault diagnosis information. Simulation results show that the proposed approach is helpful in detecting the root cause of failure and is more correct than single fault diagnosis method.