Articles | Volume 4, issue 2
J. Sens. Sens. Syst., 4, 305–311, 2015
https://doi.org/10.5194/jsss-4-305-2015

Special issue: Sensor/IRS2 2015

J. Sens. Sens. Syst., 4, 305–311, 2015
https://doi.org/10.5194/jsss-4-305-2015

Regular research article 19 Oct 2015

Regular research article | 19 Oct 2015

A novel approach for detecting HMDSO poisoning of metal oxide gas sensors and improving their stability by temperature cycled operation

M. Schüler, T. Sauerwald, and A. Schütze M. Schüler et al.
  • Laboratory for Measurement Technology, Saarland University, Saarbrücken, Germany

Abstract. In this paper we study the effect of hexamethyldisiloxane (HMDSO) vapor on an SnO2-based gas sensor (GGS 1330, UST Umweltsensortechnik GmbH, Geschwenda, Germany) in a temperature cycled operation (TCO). We show that HMDSO poisoning can be quantified at early stages (85 to 340 ppm × min) with a resolution of ±85 ppm × min using TCO. This novel approach for sensor self-monitoring provides a simple method for early detection of HMDSO poisoning. It is thereby possible to detect poisoning before the sensor function is strongly impaired. In this paper we show that by using an appropriate normalization of the sensor data, the stability of gas discrimination by linear discriminant analysis (LDA) can be improved, which in turn facilitates a more accurate determination of the poisoning state by a hierarchical LDA discrimination.

For a specific temperature cycle and feature extraction approach, we show that identification of ethanol and carbon monoxide is still possible after poisoning with 900 ppm × min HMDSO, i.e. a HMDSO poisoning dose more than twice as high as required by DIN EN 50194-1.

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Short summary
We study the effect of HMDSO vapor on an SnO2-based gas sensor in temperature cycled operation (TCO). The poisoning can be quantified at early stages with a resolution of ±85 ppm*min using TCO. This approach provides a simple method for early detection of HMDSO poisoning. The stability of gas discrimination by linear discriminant analysis (LDA) can be improved using normalization, which in turn facilitates a more accurate determination of the poisoning state by hierarchical LDA discrimination.
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