Abstract
In this paper we introduce a system for early classification of several fault modes in a continuous process. Early fault classification is basic in supervision and diagnosis systems, since a fault could arise at any time, and the system must identify the fault as soon as possible. We present a computational framework to deal with the problem of early fault classification using Case-Based Reasoning. This work illustrates different techniques for case retrieval and reuse that have been applied at different times of fault evolution. The technique has been tested for a set of fourteen fault classes simulated in a laboratory plant.
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Bregón, A., Simón, M.A., Rodríguez, J.J., Alonso, C., Pulido, B., Moro, I. (2006). Early Fault Classification in Dynamic Systems Using Case-Based Reasoning. In: Marín, R., Onaindía, E., Bugarín, A., Santos, J. (eds) Current Topics in Artificial Intelligence. CAEPIA 2005. Lecture Notes in Computer Science(), vol 4177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881216_23
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DOI: https://doi.org/10.1007/11881216_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45914-9
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