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Analyse et modélisation d’un compresseur à piston à vitesse variable utilisant les réseaux de neurones artificiels (ANN).

Analysis and modeling of a variable speed reciprocating compressor using ANN.

Auteurs : LEDESMA S., BELMAN-FLORES J. M., BARROSO-MALDONADO J. M.

Type d'article : Article, Article de la RIF

Résumé

This work presents the empirical study of a reciprocating compressor using Artificial Intelligence to model it. Several artificial neural networks were used to model three energy parameters of the compressor with high precision. The number of neurons in each ANN was optimized to use the minimum number of neurons without compromising accuracy; very few neurons were used when comparing with other works. Computer simulations show that the ANN model for the mass flow rate has the highest accuracy when compared with the models for the discharge temperature and power consumption. These simulations also illustrate that the ANN model for the discharge temperature presented the lowest accuracy. Using the ANN model, 3D plots were built to analyze the energy behavior of the compressor.

Documents disponibles

Format PDF

Pages : 190-197

Disponible

  • Prix public

    20 €

  • Prix membre*

    Gratuit

* meilleur tarif applicable selon le type d'adhésion (voir le détail des avantages des adhésions individuelles et collectives)

Détails

  • Titre original : Analysis and modeling of a variable speed reciprocating compressor using ANN.
  • Identifiant de la fiche : 30016297
  • Langues : Anglais
  • Source : International Journal of Refrigeration - Revue Internationale du Froid - vol. 59
  • Date d'édition : 11/2015

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