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 |
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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 |
| _version_ | 1818289625070829568 |
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| author | Lentka Łukasz Smulko Janusz M. Ionescu Radu Granqvist Claes G. Kish Laszlo B. |
| author_facet | Lentka Łukasz Smulko Janusz M. Ionescu Radu Granqvist Claes G. Kish Laszlo B. |
| author_sort | Lentka Łukasz |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-13T02:15:15Z |
| format | Article |
| id | doaj.art-25d81736dc934888b7fd37e000c959a3 |
| institution | Directory Open Access Journal |
| issn | 2300-1941 |
| language | English |
| last_indexed | 2024-12-13T02:15:15Z |
| publishDate | 2015-09-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | Metrology and Measurement Systems |
| spelling | doaj.art-25d81736dc934888b7fd37e000c959a32022-12-22T00:02:54ZengPolish Academy of SciencesMetrology and Measurement Systems2300-19412015-09-0122334135010.1515/mms-2015-0039mms-2015-0039Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression AlgorithmLentka Łukasz0Smulko Janusz M.1Ionescu Radu2Granqvist Claes G.3Kish Laszlo B.41) Gdańsk University of Technology, Faculty of Electronics, Telecommunications and Informatics, G. Narutowicza 11/12, 80-233 Gdańsk, Poland1) Gdańsk University of Technology, Faculty of Electronics, Telecommunications and Informatics, G. Narutowicza 11/12, 80-233 Gdańsk, Poland2) Rovira i Virgili University, ETSE-DEEEA, Department of Electronics, Carrer de l`Escorxador, 43003 Tarragona, Spain3) Uppsala University, Department of Engineering Sciences, P.O. Box 534, SE-75121 Uppsala, Sweden4) Texas AThis 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.http://www.degruyter.com/view/j/mms.2015.22.issue-3/mms-2015-0039/mms-2015-0039.xml?format=INTLS-SVM algorithmresistance gas sensorfluctuation enhanced sensinggas detection |
| spellingShingle | Lentka Łukasz Smulko Janusz M. Ionescu Radu Granqvist Claes G. Kish Laszlo B. Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm Metrology and Measurement Systems LS-SVM algorithm resistance gas sensor fluctuation enhanced sensing gas detection |
| title | Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm |
| title_full | Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm |
| title_fullStr | Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm |
| title_full_unstemmed | Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm |
| title_short | Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm |
| title_sort | determination of gas mixture components using fluctuation enhanced sensing and the ls svm regression algorithm |
| topic | LS-SVM algorithm resistance gas sensor fluctuation enhanced sensing gas detection |
| url | http://www.degruyter.com/view/j/mms.2015.22.issue-3/mms-2015-0039/mms-2015-0039.xml?format=INT |
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