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Détection des anomalies et méthode de diagnostic pour l'équipement de chauffage, de ventilation et de conditionnement d'air dans des immeubles.

[ In Korean. / En coréen.]

Auteurs : HAN D. W., CHANG Y. S.

Résumé

Automated control methods for building HVAC systems have been widely applied. In a modern control system, we need to detect and to cope with abnormal event of target system using intelligent control systems. The automated fault detection and diagnosis (FDD) are the first step for maintenance decision of HVAC equipments. In this study, an FDD algorithm was proposed using the general pattern classifier method that can be applied to various faults of HVAC equipments. The experiment and simulation model for a water chiller system was developed in order to obtain characteristic data of water chiller system under normal and faulty operation. Fault detection performance by FDD algorithm of a water chiller was tested using data from the experiment and simulation model. In this research, sensitivity analysis of fault detection was carried out with respect to fault progress. FDD algorithm proposed in this study was found to indicate each failure modes accurate.

Détails

  • Titre original : [ In Korean. / En coréen.]
  • Identifiant de la fiche : 2009-1212
  • Langues : Coréen
  • Source : 3e Congrès coréen du froid.
  • Date d'édition : 19/03/2009

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