Please use this identifier to cite or link to this item: doi:10.22028/D291-37451
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Title: Impedance based detection of HMDSO poisoning in metal oxide gas sensors
Author(s): Schüler, Marco
Schneider, Tizian
Sauerwald, Tilman
Schütze, Andreas
Language: English
Title: Technisches Messen : tm
Volume: 84
Issue: 11
Startpage: 697
Endpage: 705
Publisher/Platform: De Gruyter
Year of Publication: 2017
DDC notations: 620 Engineering and machine engineering
Publikation type: Journal Article
Abstract: A commercial SnO2-based metal oxide gas sensor (UST GGS 1330) operated at a constant temperature of 170 ℃ was evaluated in a frequency range from 40 Hz to 110 MHz using an Agilent 4294A high precision impedance analyzer. The sensor was exposed to carbon monoxide and ethanol at three concentrations each (1, 2 and 5 ppm) and at humidities of 40%rh and 60%rh. After application of the test gas profile, the sensor was repeatedly poisoned with 9.3 ppm of HMDSO for 20 min, and the gas test was repeated up to an overall poisoning dose of 930 ppm min (i.e. five times). Impedance data exhibit characteristic features for the different test gases as well as for sensor poisoning. Using Haar-Wavelet transformation and Adaptive Linear Approximation for feature extraction followed by feature selection with Recursive Feature Elimination Support Vector Machines a total classification rate well above 98% was achieved for test gas type and concentration as well as sensor poisoning state with linear discriminant analysis and a Mahalonobis distance classifier.
DOI of the first publication: 10.1515/teme-2017-0002
URL of the first publication: https://www.degruyter.com/document/doi/10.1515/teme-2017-0002/html
Link to this record: urn:nbn:de:bsz:291--ds-374517
hdl:20.500.11880/33872
http://dx.doi.org/10.22028/D291-37451
ISSN: 2196-7113
0171-8096
Date of registration: 29-Sep-2022
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Systems Engineering
Professorship: NT - Prof. Dr. Andreas Schütze
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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