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.
The influence of oxygen partial pressure and of temperature upon the conductance and Seebeck e.m.f. transients at rapid changes in humidity was investigated. The results are discussed and interpreted within the model formerly proposed for the interaction of SnO₂ with water vapours based on several reaction paths supporting also the ptype conduction.
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