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Authors: M. Traore ; E. Duviella and S. Lecoeuche

Affiliation: Ecole des Mines de Douai, France

Keyword(s): Supervision, Pattern Recognition, Non-stationary data, AUDyC.

Related Ontology Subjects/Areas/Topics: Control and Supervision Systems ; Informatics in Control, Automation and Robotics ; Robotics and Automation

Abstract: In this paper, we propose a supervision method which aims at determining pertinent indicators to optimize predictive maintenance strategies. The supervision method, based on the AUto-adaptative and Dynamical Clustering technique (AUDyC), consists in classifying in real time measured data into classes representative of the operating modes of the process. This technique also allows the detection and the tracking of the slow evolutions of the process modes. Based on the AUDyC technique, a method is proposed to estimate the probabilities of the failure occurence of components in real time. This method is illustrated on the real case of a temperature controller.

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Paper citation in several formats:
Traore, M.; Duviella, E. and Lecoeuche, S. (2009). DYNAMICAL CLUSTERING TECHNIQUE TO ESTIMATE THE PROBABILITY OF THE FAILURE OCCURRENCE OF PROCESS SUBJECTED TO SLOW DEGRADATION. In Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-674-000-9; ISSN 2184-2809, SciTePress, pages 360-365. DOI: 10.5220/0002250003600365

@conference{icinco09,
author={M. Traore. and E. Duviella. and S. Lecoeuche.},
title={DYNAMICAL CLUSTERING TECHNIQUE TO ESTIMATE THE PROBABILITY OF THE FAILURE OCCURRENCE OF PROCESS SUBJECTED TO SLOW DEGRADATION},
booktitle={Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2009},
pages={360-365},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002250003600365},
isbn={978-989-674-000-9},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - DYNAMICAL CLUSTERING TECHNIQUE TO ESTIMATE THE PROBABILITY OF THE FAILURE OCCURRENCE OF PROCESS SUBJECTED TO SLOW DEGRADATION
SN - 978-989-674-000-9
IS - 2184-2809
AU - Traore, M.
AU - Duviella, E.
AU - Lecoeuche, S.
PY - 2009
SP - 360
EP - 365
DO - 10.5220/0002250003600365
PB - SciTePress