A Hybrid Approach of Fault Inference and Fault Identification for Aircraft Fault Diagnosis

Abstract

Logical inference based on a cockpit instruments fault tree (FT) 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. To use these correlations, the inference and MM method can share fault information. Simulation results show that the proposed diagnosis approach is helpful in detecting the root cause of failure and is more correct than single fault inference method.