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Modèle de la diminution d'efficacité des compresseurs simples et à vitesse variable à l'aide de réseaux neuronaux.

Loss-efficiency model of single and variable-speed compressors using neural networks.

Auteurs : YANG L., ZHAO L. X., ZHANG C. L., et al.

Type d'article : Article, Article de la RIF

Résumé

The compressor is the critical component to the performance of a vapour-compression refrigeration system. The loss-efficiency model including the volumetric efficiency and the isentropic efficiency is widely used for representing the compressor performance. A neural network loss-efficiency model is developed to simulate the performance of positive displacement compressors like the reciprocating, screw and scroll compressors. With one more input, frequency, it can be easily extended to the variable speed compressors. The three-layer polynomial perceptron network is developed because the polynomial transfer function is found very effective in training and free of over-learning. The selection of input parameters of neural networks is also found critical to the network prediction accuracy. The proposed neural networks give less than 0.4% standard deviations and plus or minus 1.3% maximum deviations against the manufacturer data.

Documents disponibles

Format PDF

Pages : pp. 1423-1432

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    20 €

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    Gratuit

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Détails

  • Titre original : Loss-efficiency model of single and variable-speed compressors using neural networks.
  • Identifiant de la fiche : 2009-2006
  • Langues : Anglais
  • Source : International Journal of Refrigeration - Revue Internationale du Froid - vol. 32 - n. 6
  • Date d'édition : 09/2009

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