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Habilitation à diriger des recherches

Contribution à la Surveillance des Systèmes de Production en Utilisant l'Intelligence Artificielle

Abstract : This thesis treats about production systems dynamic monitoring using artificial intelligent techniques.
The main contributions consist in a new dynamic neural network called recurrent radial basis function network, able to offer very intereting and promissiong solutions for dynamic monitoring, in particular for degradation and false alarm early detection.
The production system's fault tree (FT) is also exploited using a fuzzy Petri net. This approach permit us to do a dynamic monitoring of the degradation propagation into the system, transforming the fuzzy temporal information in a critical degradation predictor.
At the end, the last developmens in the field of diagosis aid are presented. The neuro-fuzzy system also studied, developped and prototyped is used in collaboration with industrial maintenance tools like fault tree and FMECA.
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Habilitation à diriger des recherches
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Contributor : Daniel Racoceanu <>
Submitted on : Thursday, March 2, 2006 - 6:46:29 AM
Last modification on : Monday, November 16, 2020 - 10:58:04 AM
Long-term archiving on: : Saturday, April 3, 2010 - 10:40:04 PM

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Daniel Racoceanu. Contribution à la Surveillance des Systèmes de Production en Utilisant l'Intelligence Artificielle. Automatique / Robotique. Université de Franche-Comté, 2006. ⟨tel-00011708⟩

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