FDI WITH NEURAL AND NEUROFUZZY APPROACHES - Application to Damadics

Y. Kourd, N. Guersi, D. Lefebvre

Abstract

Fault diagnosis is a major challenge for complex systems as long as it increases the safety and productivity. This work concerns faults diagnosis, based on artificial intelligence, neural networks, and fuzzy logic. Thanks to an associative memory, neural networks have good capacities of organization, approximation and classification. Combined with fuzzy logic, neural networks are an effective tool for system modelling, fault detection and fault diagnosis. This paper illustrates the potential of these tools for the modelling and the diagnosis of an industrial actuator (DAMADICS benchmark).

References

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Paper Citation


in Harvard Style

Kourd Y., Guersi N. and Lefebvre D. (2010). FDI WITH NEURAL AND NEUROFUZZY APPROACHES - Application to Damadics . In Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-8425-01-0, pages 368-372. DOI: 10.5220/0002928103680372


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - FDI WITH NEURAL AND NEUROFUZZY APPROACHES - Application to Damadics
SN - 978-989-8425-01-0
AU - Kourd Y.
AU - Guersi N.
AU - Lefebvre D.
PY - 2010
SP - 368
EP - 372
DO - 10.5220/0002928103680372


in Bibtex Style

@conference{icinco10,
author={Y. Kourd and N. Guersi and D. Lefebvre},
title={FDI WITH NEURAL AND NEUROFUZZY APPROACHES - Application to Damadics},
booktitle={Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2010},
pages={368-372},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002928103680372},
isbn={978-989-8425-01-0},
}