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Sensors 2018, 18(2), 550; doi:10.3390/s18020550

On the Temporal Stability of Analyte Recognition with an E-Nose Based on a Metal Oxide Sensor Array in Practical Applications

1
Breitmeier Messtechnik GmbH, Englerstr. 27, 76275 Ettlingen, Germany
2
Laboratory of Sensors and Microsystems, Yuri Gagarin State Technical University of Saratov, 77 Polytechnicheskaya str., 410054 Saratov, Russia
3
National University of Science and Technology MISiS, 4 Leninskiy pr., 119991 Moscow, Russia
4
Institute of Microstructure Technology, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
5
Science and Technology of Nanosystems, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
6
Faculty of Engineering, Kyrgyz-Turkish Manas University, Mira Avenue 56, 720044 Bishkek, Kyrgyz Republic
*
Authors to whom correspondence should be addressed.
Received: 18 November 2017 / Revised: 28 January 2018 / Accepted: 7 February 2018 / Published: 11 February 2018
(This article belongs to the Special Issue Artificial Olfaction and Taste)
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Abstract

The paper deals with a functional instability of electronic nose (e-nose) units which significantly limits their real-life applications. Here we demonstrate how to approach this issue with example of an e-nose based on a metal oxide sensor array developed at the Karlsruhe Institute of Technology (Germany). We consider the instability of e-nose operation at different time scales ranging from minutes to many years. To test the e-nose we employ open-air and headspace sampling of analyte odors. The multivariate recognition algorithm to process the multisensor array signals is based on the linear discriminant analysis method. Accounting for the received results, we argue that the stability of device operation is mostly affected by accidental changes in the ambient air composition. To overcome instabilities, we introduce the add-training procedure which is found to successfully manage both the temporal changes of ambient and the drift of multisensor array properties, even long-term. The method can be easily implemented in practical applications of e-noses and improve prospects for device marketing. View Full-Text
Keywords: electronic nose; instability; long-term stability; ambient air; meat quality control; honey recognition; linear discriminant analysis electronic nose; instability; long-term stability; ambient air; meat quality control; honey recognition; linear discriminant analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kiselev, I.; Sysoev, V.; Kaikov, I.; Koronczi, I.; Adil Akai Tegin, R.; Smanalieva, J.; Sommer, M.; Ilicali, C.; Hauptmannl, M. On the Temporal Stability of Analyte Recognition with an E-Nose Based on a Metal Oxide Sensor Array in Practical Applications. Sensors 2018, 18, 550.

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