Online real-time health management for aerial electrical power system

To address the problem of observational information uncertainties and task deadlines met in the online real-time health management for aerial electrical power system, the latest HM algorithms in China and aboard were summarized which were focused on the Bayesian networks (BNs) and compiling Bayesian network, and then an approach of online real-time health management for aerial electrical power system was proposed. In this approach, the object-oriented method was used to develop BN health model based on the system structure model, and then the BN was offline compiled into the arithmetic circuit (AC) health model using global variable elimination algorithm, subsequently, the resulting circuit can be applied to calculate the posterior probability of system health. The experimental results show that the AC health model, compared with the BN health model, not only precisely online real-time isolates the system faults, but also meets the strict time deadlines of HM under the condition of observational information uncertainties.