Contribution à l'estimation de la durée de vie résiduelle des systèmes en présence d'incertitudes

Abstract : Predictive maintenance strategies can help reduce the ever-growing maintenance costs, but their implementation represents a major challenge. Indeed, it requires to evaluate the health state of the component of the system and to prognosticate the occurrence of a future failure. This second step consists in estimating the remaining useful life (RUL) of the components, in Other words, the time they will continue functioning properly. This RUL estimation holds a high stake because the precision and accuracy of the results will influence the relevance and effectiveness of the maintenance operations. Many methods have been developed to prognosticate the remaining useful life of a component. Each one has its own particularities, advantages and drawbacks. The present work proposes a general methodology for component RUL estimation. The objective i to develop a method that can be applied to many different cases and situations and does not require big modifications. Moreover, several types of uncertainties are being dealt With in order to improve the accuracy of the prognostic. The proposed methodology can help in the maintenance decision making process. Indeed, it is possible to select the optimal moment for a required intervention thanks to the estimated RUL. Furthermore, dealing With the uncertainties provides additional confidence into the prognostic results.
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Adrien Delmas. Contribution à l'estimation de la durée de vie résiduelle des systèmes en présence d'incertitudes. Performance et fiabilité [cs.PF]. Université de Technologie de Compiègne, 2019. Français. ⟨NNT : 2019COMP2476⟩. ⟨tel-02178913⟩

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