On-line nitrogen CARS thermometry on a 130 kW burner by using a neural network approach

R. Fantoni, F. Colao, L. De Dominicis, M. Giorgi, M. D'Apice, S. Giammartini, H.J.L. Van Der Steen

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4 Citations (Scopus)

Abstract

The application of a neural network approach to on-line nitrogen CARS thermometry was developed for a standard setup with PC-based data acquisition in a LABview environment. The method utilized is based on initial clustering of the training network. The main advantage of the neural network method is speed with the potential for on-line temperature extraction. Results of space-resolved temperature measurements are presented in the case of an industrial CH4-air burner operating at atmospheric pressure. The resulting temperatures were compared with values extracted from the data using conventional least-squares fitting. Copyright (C) 2000 John Wiley and Sons, Ltd.
Original languageEnglish
Pages (from-to)697 - 701
Number of pages5
JournalJournal of Raman Spectroscopy
Volume31
Issue number8-9
DOIs
Publication statusPublished - 2000
Externally publishedYes

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All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Spectroscopy

Cite this

Fantoni, R., Colao, F., De Dominicis, L., Giorgi, M., D'Apice, M., Giammartini, S., & Van Der Steen, H. J. L. (2000). On-line nitrogen CARS thermometry on a 130 kW burner by using a neural network approach. Journal of Raman Spectroscopy, 31(8-9), 697 - 701. https://doi.org/10.1002/1097-4555(200008/09)31:8/9<697::AID-JRS595>3.0.CO;2-M