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

Number: pap. 1650

Author(s) : QUOILIN S., SCHROUFF J.

Summary

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.

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Pages: 8 p.

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Details

  • Original title: Assessing the quality of experimental data with Gaussian processes: example with an injection scroll compressor.
  • Record ID : 30014241
  • Languages: English
  • Source: 2014 Purdue Conferences. 22nd International Compressor Engineering Conference at Purdue.
  • Publication date: 2014/07/14

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