Online real-time health management for aerial fuel delivery system

To address the problems of observational information uncertainties and task deadlines encountered in the online real-time health management(HM) for aerial fuel system(AFS), the latest HM algorithms in China and aboard were researched, and an approach for health modeling and online real-time reasoning of AFS was proposed. The object-oriented method was used to develop BN health model based on the system structure model, and the global variable elimination(GVE) algorithm was applied to the offline compilation of this BN into an arithmetic circuit(AC) health model. The simulation results show that the AC, compared with the Bayesian network, can not only provide precisely online diagnosis of system faults, but also effectively meet the strict time deadlines for HM requirements, under the condition of observational information uncertainties.