Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm
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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Polish Academy of Sciences
2015-09-01
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| Series: | Metrology and Measurement Systems |
| Subjects: | |
| Online Access: | http://www.degruyter.com/view/j/mms.2015.22.issue-3/mms-2015-0039/mms-2015-0039.xml?format=INT |
| Summary: | 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. |
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| ISSN: | 2300-1941 |