Gas recognition using a neural network approach to plasma optical emission spectroscopy

Mark Hyland*, Davide Mariotti, Werner Dubitzky, James A. McLaughlin, Paul Maguire

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

6 Citations (Scopus)

Abstract

A system has been developed which enables the detection and recognition of various gases. Plasma emission spectroscopy has been used to record spectra from volatile species of acetone, vinegar, and coffee beans, along with air and nitrogen spectra. The spectra have been uniquely processed and fed into an artificial neural network program for training and recognition of unknown gases. The system as a whole can be grouped into the emerging and diverse area of artificial nose technology. The system has shown to provide a solution to the recognition of simple gases and odours (air, nitrogen, acetone) and could also satisfactorily recognize more complex samples (vinegar and coffee beans). Recognition is performed in seconds; this being a positive aspect for many artificial nose applications.

Original languageEnglish
Pages (from-to)246-252
Number of pages7
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4120
DOIs
Publication statusPublished - 13 Oct 2000
EventApplications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation III - San Diego, USA
Duration: 31 Jul 20001 Aug 2000

Keywords

  • Plasma emission spectroscopy
  • artificial nose applications
  • unknown gas detection

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