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Contribution au pronostic industriel : intégration de la confiance à un modèle prédictif neuro-flou.

Abstract : Industrial prognostic is nowadays recognized as a key feature to reinforce the dependability of equipments while reducing maintenance costs. However, it can be dicult to implement an ecient prognostic tool since the lack of knowledge on the behaviour of an equipment can impede the development of classical dependability analysis. In this context, the general purpose of the work is to propose a prognostic system that starts from monitoring data and goes through useful indicators to optimize maintenance strategies. The work also aims at mitigating some problems that follow from the lack of knowledge on the degradation phenomena (amount of data, expertise in building a model). Developments are based on the use of the neuro-fuzzy system exTS as a tool to predict the state of degradation of an equipment. Its structure is partially determined, on one side, thanks to its evolving capability, and on the other side, thanks to parsimony principle : a procedure to automatically generate an accurate exTS prediction system that reaches a compromise between complexity and generalization capability is proposed. Following that, a method to rstly, a priori estimate the probability density function (pdf) of the error of prediction of the neuro-fuzzy system, and secondly propagate it to any prediction step, is also proposed and illustrated. This contribution enables to provide a condence measure on predictions and thereby to integrate uncertainty to the prognostic process. Finally, mechanisms of reliability evaluation are adapted to the predictive case in order to generate the prognostic metrics that allows optimizing maintenance strategies, notably the Remaining Useful Life (RUL).
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https://tel.archives-ouvertes.fr/tel-00542230
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Submitted on : Thursday, December 2, 2010 - 9:18:10 AM
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  • HAL Id : tel-00542230, version 1

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Mohamed El Koujok. Contribution au pronostic industriel : intégration de la confiance à un modèle prédictif neuro-flou.. Automatique / Robotique. Université de Franche-Comté, 2010. Français. ⟨tel-00542230⟩

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