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Diagnostic de panne d’un système frigorifique centrifuge au moyen d’un réseau neuronal probabiliste.

[In Chinese. / En chinois.]

Auteurs : LIANG Q., HAN H., CUI X.

Type d'article : Article

Résumé

Applies the probabilistic neural network (PNN) to diagnose seven types of typical faults for a refrigeration system, including system-level faults and component-level faults. Elaborates the establishment of the fault diagnosis model based on PNN and the optimal processes of finding out the best spread value in detail. Studies the influence of sample size on the best spread value and the correct diagnose rate. Compares the performance of the PNN and the prevailing back-propagation (BP) neural network. The results show that the overall correct diagnosis rate of the PNN model is 3.48% higher than that of the BP network, which consumes much less diagnosing time, and the diagnosis of single training with the PNN is more reliable than that of the BP network. Although the diagnosis results of these two networks show that the system-level faults is more difficult to be identified than the component-level faults, great improvement still has been observed by using PNN.

Documents disponibles

Format PDF

Pages : 101-107

Disponible

  • Prix public

    20 €

  • Prix membre*

    15 €

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

Détails

  • Titre original : [In Chinese. / En chinois.]
  • Identifiant de la fiche : 30018381
  • Langues : Chinois
  • Source : HV & AC - vol. 45 - n. 311
  • Date d'édition : 11/2015

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