Fault detection based on fractional order models: Application to diagnosis of thermal systems

Abstract : The aim of this paper is to propose diagnosis methods based on fractional order models and to validate their efficiency to detect faults occurring in thermal systems. Indeed, it is first shown that fractional operator allows to derive in a straightforward way fractional models for thermal phenomena. In order to apply classical diagno- sis methods, such models could be approximated by integer order models, but at the expense of much higher involved parameters and reduced precision. Thus, two diagnosis methods initially developed for integer order models are here extended to handle fractional order models. The first one is the generalized dynamic parity space method and the second one is the Luenberger diagnosis observer. Proposed methods are then applied to a single-input multi-output thermal testing bench and demonstrate the methods efficiency for detecting faults affecting thermal systems.
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Article dans une revue
Communications in Nonlinear Science and Numerical Simulation, Elsevier, 2014, 〈10.1016/j.cnsns.2014.03.006〉
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https://hal.archives-ouvertes.fr/hal-00980487
Contributeur : Christophe Farges <>
Soumis le : vendredi 18 avril 2014 - 10:05:57
Dernière modification le : jeudi 11 janvier 2018 - 06:26:32

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Asma Aribi, Christophe Farges, Mohamed Aoun, Pierre Melchior, Slaheddine Najar, et al.. Fault detection based on fractional order models: Application to diagnosis of thermal systems. Communications in Nonlinear Science and Numerical Simulation, Elsevier, 2014, 〈10.1016/j.cnsns.2014.03.006〉. 〈hal-00980487〉

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