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Assessing the quality of experimental data with Gaussian processes: example with an injection scroll compressor.

Numéro : pap. 1650

Auteurs : QUOILIN S., SCHROUFF J.

Résumé

This paper describes an experimental study carried out on a refrigeration scroll compressor with and without vapour injection. The test rig designed for that purposed allows evaluating the performance over a wide range of operating conditions, by varying the supply pressure, the injection pressure, the discharge pressure, the supply superheating and the injection superheating. 97 Steady-state points are measured, with a maximum isentropic efficiency of 64.1% and a maximum consumed electrical power of 13.1 kW. A critical analysis of the experimental results is then carried out to evaluate the quality of the data using a machine learning method. This method based on Gaussian Processes regression, is used to build a statistical operating map of the compressor as a function of the different inputs. This statistical operating map can then be compared to the experimental data points to evaluate their accuracy.

Documents disponibles

Format PDF

Pages : 8 p.

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 : Assessing the quality of experimental data with Gaussian processes: example with an injection scroll compressor.
  • Identifiant de la fiche : 30014241
  • Langues : Anglais
  • Source : 2014 Purdue Conferences. 22nd International Compressor Engineering Conference at Purdue.
  • Date d'édition : 14/07/2014

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