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DOI: 10.5445/IR/1000080594
Veröffentlicht am 28.02.2018

On the temporal stability of analyte recognition with an e-nose based on a metal oxide sensor array in practical applications

Kiselev, I.; Sysoev, V.; Kaikov, I.; Koronczi, I.; Tegin, R. A. A.; Smanalieva, J.; Sommer, M.; Ilicali, C.; Hauptmannl, M.

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.

Zugehörige Institution(en) am KIT Institut für Mikrostrukturtechnik (IMT)
Programm Science and Technology of Nanosystems (STN)
Publikationstyp Zeitschriftenaufsatz
Jahr 2018
Sprache Englisch
Identifikator ISSN: 1424-8220
URN: urn:nbn:de:swb:90-805949
KITopen ID: 1000080594
Erschienen in Sensors
Band 18
Heft 2
Seiten Art. Nr.: 550
Schlagworte electronic nose, instability, long-term stability, ambient air, meat quality control, honey recognition, linear discriminant analysis
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