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

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Title: Gas recognition using a neural network approach to plasma optical emission spectroscopy
Author: Hyland, Mark; Mariotti, Davide; Dubitzky, Werner; McLaughlin, James; Maguire, Paul
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 recognise more complex samples (vinegar and coffee beans). Recognition is performed in seconds; this being a positive aspect for many artificial nose applications.
Record URI: http://hdl.handle.net/1850/11430
Date: 2000

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