Structural diagnosability analysis. Application to an induction motor

Abstract : The presented research is carried out within the framework of a global industrial project “Electro-Mechanical Actuator Health Management” with french company CERTIA. The objective is the realization of an auto-diagnosis embedded module for health monitoring and reconfiguration of Electro-Mechanical Actuator (EMA) including two operating modes: Test checking before taking off (evaluation and health management, i.e evaluation of the rate of degradation) and online supervision including (i)fault detection and isolation (to avoid the irreversible jamming default for instance) and (ii) fault tolerant control and/or reconfiguration in faulty situation (how to continue to control the system en degraded mode ?). The present paper concerns the first part of the project. The innovative interest concerns use of bond graph model as unified and multidisciplinary tool not only for modeling but also for structural diagnosability analysis (which faults which may affect component including sensors can be detected an isolated ?) and sensor placement proposition to make the system diagnosable Without any need of numerical calculation. An application to an induction motor as main component in an EMA is used for illustration.
Type de document :
Communication dans un congrès
SDEMPED 2017 - 11th IEEE International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, Aug 2017, Tinos, Greece. IEEE, Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED), 2017 IEEE 11th International Symposium on, pp.1-7, 〈https://www.egr.msu.edu/sdemped2017/home〉. 〈10.1109/DEMPED.2017.8062374〉
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https://hal-centralesupelec.archives-ouvertes.fr/hal-01658216
Contributeur : Islam Boussaada <>
Soumis le : jeudi 7 décembre 2017 - 14:22:22
Dernière modification le : jeudi 11 janvier 2018 - 06:27:22

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Naouel Kaci, Belkacem Ould Bouamama, Islam Boussaada, Achour Debiane. Structural diagnosability analysis. Application to an induction motor. SDEMPED 2017 - 11th IEEE International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, Aug 2017, Tinos, Greece. IEEE, Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED), 2017 IEEE 11th International Symposium on, pp.1-7, 〈https://www.egr.msu.edu/sdemped2017/home〉. 〈10.1109/DEMPED.2017.8062374〉. 〈hal-01658216〉

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