Document IIF

Systèmes de chauffage, ventilation et conditionnement d'air : détection d'anomalies et diagnostic à l'aide d'une méthode assurée par une "support vector machine".

Model-based fault detection and diagnosis of HVAC systems using support vector machine method.

Auteurs : LIANG J., DU R.

Type d'article : Article, Article de la RIF

Résumé

Preventive maintenance plays a very important role in the modern HVAC systems for guaranteeing the thermal comfort, energy saving and reliability. Its key is a cost-effective fault detection and diagnosis (FDD) method. To achieve this goal, this paper proposes a new method by combining the model-based FDD method and the support vector machine (SVM) method. A lumped-parameter model of a single zone HVAC system is developed first, and then the characteristics of three major faults, including the recirculation damper stuck, cooling coil fouling/block and supply fan speed decreasing, are investigated by computer simulation. It is found that the supply air temperature, mixed air temperature, outlet water temperature and control signal are sensitive to the faults and can be selected as the fault indicators. Based on the variations of the system states under the normal and faulty conditions of different degrees, the faults can be detected efficiently by using the residual analysis method. Furthermore, a multi-layer SVM classifier is developed, and the diagnosis results show that this classifier is effective with high accuracy. As a result, the presented model-based fault detection and diagnosis method can help to maintain the health of the HVAC systems, reduce energy consumption and maintenance cost.

Documents disponibles

Format PDF

Pages : 1104-1114

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 : Model-based fault detection and diagnosis of HVAC systems using support vector machine method.
  • Identifiant de la fiche : 2007-2741
  • Langues : Anglais
  • Source : International Journal of Refrigeration - Revue Internationale du Froid - vol. 30 - n. 6
  • Date d'édition : 09/2007

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