Gas identification using micro gas sensor array and neural-network pattern recognition

In order to identify CH 3SH, (CH 3) 3H, C 2H 5OH and CO gases in the concentration range of 0.1 to 100 ppm, a gas recognition system using a gas sensor array and neural-network pattern recognition has been fabricated. The sensor array consists of such thin film oxide semiconductor sensing materials...

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Bibliographic Details
Published in:Sensors and actuators. B, Chemical Chemical, 1996-07, Vol.33 (1), p.68-71
Main Authors: Hong, Hyung-Ki, Shin, Hyun Woo, Park, Hyeon Soo, Yun, Dong Hyun, Kwon, Chul Han, Lee, Kyuchung, Kim, Sung-Tae, Moriizumi, Toyosaka
Format: Article
Language:English
Subjects:
Analytical chemistry
Back-propagation
Chemistry
Exact sciences and technology
Gas identification
Gas sensor array
General, instrumentation
Pattern recognition
Power consumption
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Summary:In order to identify CH 3SH, (CH 3) 3H, C 2H 5OH and CO gases in the concentration range of 0.1 to 100 ppm, a gas recognition system using a gas sensor array and neural-network pattern recognition has been fabricated. The sensor array consists of such thin film oxide semiconductor sensing materials as 1 wt% Pd-doped SnO 2, 6 wt% Al 2O 3-doped ZnO, WO 3 and ZnO. The principal component analysis and the neural-network pattern recognition analysis were used for the discrimination of gas species and concentrations. Good separation among gases and concentrations was obtained using the principal component analysis. The recognition probability of the neural-network was 100% for each 5 trials of 12 gas samples.
ISSN:0925-4005
1873-3077
DOI:10.1016/0925-4005(96)01892-8