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Información tecnológica

versión On-line ISSN 0718-0764

Resumen

SARMIENTO, Henry O; ISAZA, Claudia V; KEMPOWSKY-HAMON, Tatiana  y  LELANN, Marie-Veronique. Estimation of Functional States in Complex Processes Based on Fuzzy Clustering. Inf. tecnol. [online]. 2013, vol.24, n.2, pp.79-98. ISSN 0718-0764.  http://dx.doi.org/10.4067/S0718-07642013000200010.

This paper presents a methodology to predict functional states in complex processes from the estimation of fuzzy membership degrees. The proposal integrates a static measure, such as the result of a fuzzy classifier trained with historical process data, and an estimation algorithm based on Markov theory for discrete events. The proposal, which can be integrated to the monitoring of complex systems, provides two stages: an off-line training stage to define the fuzzy classifier and the estimator; and an online stage where the classification of the current process situation and the estimation of the next functional state are performed. The proposal for the estimation of functional states allows using any fuzzy clustering method that provides the information required by the methodology. The proposed methodology was successfully tested on a monitoring system for a power transmission line and in the monitoring of a boiler system.

Palabras clave : functional state prediction; fuzzy classifier; fuzzy clustering; Markov's chains.

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