| 摘要 |
A method for integrating the function models of a health management system for a vehicle e.g. aircraft (2) where the vehicle has multiple systems (4) connected to a communications network (6) and the multiple systems (4) send at least one of status messages and raw data regarding at least some of the operational data of the multiple systems (4) and making a determination of a health function of the vehicle (2), comprises the use of probabilistic graphical models (PGMs) as a framework for model integration for the Integrated Vehicle Health Management (IVHM) system and provide a method for learning a range of PGM models from the historical data. The type of model that can be represented by a PGM include: Bayesian networks, Markov models, Kalman filter, probabilistic treatment of Principal Component Analysis, Gaussian and discrete mixture models. A mixture model learning module is implemented that takes as inputs historic data, configuration parameters and a set of conditional discrete variables that essentially describes the model structure.
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