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

Hyland, M, Mariotti, D, Dubitzky, W, McLaughlin, JAD and Maguire, PD (2000) Gas recognition using a neural network approach to plasma optical emission spectroscopy. In: APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION III, SAN DIEGO. SPIE-INT SOC OPTICAL ENGINEERING. Vol 4120 5 pp. [Conference contribution]

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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 (ait, nitrogen, acetone) and could also satisfactorily recognise more complex samples (vinegar and coffee beans). Recognition is performed in seconds; this being a positive aspect for many artificial nose applications.

Item Type:Conference contribution (Paper)
Keywords:artificial nose; gas sensing; plasma spectroscopy; artificial neural network
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Engineering
Research Institutes and Groups:Engineering Research Institute
Engineering Research Institute > Nanotechnology & Integrated BioEngineering Centre (NIBEC)
ID Code:7449
Deposited By: Professor Paul Maguire
Deposited On:28 Jun 2011 07:59
Last Modified:28 Jun 2011 07:59

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