Partager

Document IIF

Une approche semi-supervisée fondée sur les données pour la détection des fuites de frigorigènes dans les refroidisseurs.

A semi-supervised data-driven approach for chiller refrigerant leakage detection.

Numéro : 0005

Auteurs : FENG Z., WANG L., MA X., JIANG Z., CHANG B.

Résumé

It’s very difficult to design a completely sealed chiller system, so refrigerant leakage is almost the most common fault in a positive pressure cycle. When a refrigerant leak occurs, chillers will have higher power consumption, even causing health and safety accidents in a closed environment. Leaking refrigerants with high global warming potential (GWP) will accelerate the greenhouse effect. This study presents a semi-supervised machine learning approach to detect refrigerant leakageand all data used for detecting leakage are from pre-installed sensors. A sophisticated experimental method was designed to collect data from a centrifugal chiller and the algorithm of anomaly detection using long short-term memory (LSTM-AD)is discussed with reconstruction error. The LSTMencoder and decoder models are trained on normal data and is used to detect leakage. It’sverified that detection sensitivity can reach 6% and the best detection coverage for leakage 6%, 11% and 16% are respectively 66%, 95% and 95%.

Documents disponibles

Format PDF

Pages : 8 p.

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 : A semi-supervised data-driven approach for chiller refrigerant leakage detection.
  • Identifiant de la fiche : 30031015
  • Langues : Anglais
  • Sujet : Technologie
  • Source : 3rd IIR conference on HFO Refrigerants and low GWP Blends. Shanghai, China.
  • Date d'édition : 05/04/2023
  • DOI : http://dx.doi.org/10.18462/iir.HFO2023.0005

Liens


Voir d'autres communications du même compte rendu (28)
Voir le compte rendu de la conférence

Indexation