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A Procedure for Failure Prognostic in Dynamic Systems

Abstract In maintenance field, many developments exist to support the prognostic activity. However, the implementation of an adequate and efficient prognostic tool can be a non trivial task as it is difficult to provide effective models of dynamic systems including the inherent uncertainty of prognostic. In this context, the purpose of the paper is to propose a procedure to generate a prognostic model. The work is based on the integration of bond graph tool and Dynamic Bayesian Networks. The first one provides a dynamic model of the system, and the second ones, thanks to their inference capability, enable to take into account uncertainty and are well suitable to perform diagnosis and prognostic. The proposed procedure is illustrated on an hydromechanical system.