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Prévision du givrage des batteries d'évaporateurs de meubles de vente de supermarchés, utilisant les réseaux neuronaux artificiels.

Frost prediction on evaporator coils of supermarket display cabinets using artificial neural networks.

Auteurs : DATTA D., TASSOU S. A., MARRIOTT D.

Résumé

Defrosting in supermarket refrigeration systems is normally controlled by a preset time cycle with most display cabinets timed to defrost every 6 hours. It is widely acknowledged that timed defrost may cause a number of unnecessary defrost cycles and this reduces the energy efficiency of refrigeration systems as well as the accuracy of temperature control of the cases. The paper investigates the possibility of modelling the amount of frost on the coil by using neural networks and proposes a demand defrost method based on it which should overcome the disadvantages of other demand defrost approaches.

Détails

  • Titre original : Frost prediction on evaporator coils of supermarket display cabinets using artificial neural networks.
  • Identifiant de la fiche : 1999-3734
  • Langues : Anglais
  • Source : CLIMA 2000, Brussels 1997, August 30 to September 2, Congress Palace.
  • Date d'édition : 08/1997
  • Document disponible en consultation à la bibliothèque du siège de l'IIF uniquement.

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