DETERMINATION OF GAS MIXTURE COMPONENTS USING FLUCTUATION ENHANCED SENSING AND THE LS-SVM REGRESSION ALGORITHM
2015 (English)In: METROLOGY AND MEASUREMENT SYSTEMS, ISSN 0860-8229, Vol. XXII, no 3, 341-350 p.Article in journal (Refereed) Published
This paper analyses the effectiveness of determining gas concentrations by using a prototype WO3 resistive gas sensor together with fluctuation enhanced sensing. We have earlier demonstrated that this method can determine the composition of a gas mixture by using only a single sensor. In the present study, we apply Least-Squares Support-Vector-Machine-based (LS-SVM-based) nonlinear regression to determine the gas concentration of each constituent in a mixture. We confirmed that the accuracy of the estimated gas concentration could be significantly improved by applying temperature change and ultraviolet irradiation of the WO3 layer. Fluctuation-enhanced sensing allowed us to predict the concentration of both component gases.
Place, publisher, year, edition, pages
2015. Vol. XXII, no 3, 341-350 p.
LS-SVM algorithm, resistance gas sensor, fluctuation enhanced sensing, gas detection
Other Engineering and Technologies
IdentifiersURN: urn:nbn:se:uu:diva-265625DOI: 10.1515/mms-2015-0039ISI: 000361772200002OAI: oai:DiVA.org:uu-265625DiVA: diva2:867000
FunderEU, FP7, Seventh Framework Programme, 267234