We developed a computer-controlled gas mixing system that provides automated test procedures for the characterization of gas sensors. The focus is the generation of trace gases (e.g. VOCs like benzene or naphthalene) using permeation furnaces and pre-dilution of test gases. With these methods, the sensor reaction can be analyzed at very low gas concentrations in the ppb range (parts per billion) and even lower. The pre-dilution setup enables to cover a high concentration range (1:62 500) within one test procedure. Up to six test gases, humidity, oxygen content, total flow and their variation over time can be controlled via a LabVIEW-based user-interface.

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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.

Abstract. For the self-test of semiconductor gas sensors, we combine two multi-signal processes: temperature-cycled operation (TCO) and electrical impedance spectroscopy (EIS). This combination allows one to discriminate between irreversible changes of the sensor, i.e., changes caused by poisoning, as well as changes in the gas atmosphere. To integrate EIS and TCO, impedance spectra should be acquired in a very short time period, in which the sensor can be considered time invariant, i.e., milliseconds or less. For this purpose we developed a Fourier-based high-speed, low-cost impedance spectroscope. It provides a binary excitation signal through an FPGA (field programable gate array), which also acquires the data. To determine impedance spectra, it uses the ETFE (empirical transfer function estimate) method, which calculates the impedance by evaluating the Fourier transformations of current and voltage. With this approach an impedance spectrum over the range from 61 kHz to 100 MHz is acquired in ca. 16 μs. We carried out TCO–EIS measurements with this spectroscope and a commercial impedance analyzer (Agilent 4294A), with a temperature cycle consisting of six equidistant temperature steps between 200 and 450 °C, with lengths of 30 s (200 °C) and 18 s (all others). Discrimination of carbon monoxide (CO) and methane (CH4) is possible by LDA (linear discriminant analysis) using either TCO or EIS data, thus enabling a validation of results by comparison of both methods.

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