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Etude d'un système multicapteur pour la détection sélective des gaz

Abstract : Chemical sensors based on metallic oxide undergo a significant lack of selectivity to gases. To overcome this problem, we proposed a solution based on the electronic nose approach, i.e. the combination of several sensors with appropriate pattern recognition methods. A semi-automatic test bench including a matrix composed of several commercial gas sensors was carried out. We used two sensor heating procedures (isotherm mode and temperature modulation mode). Principal component analysis and artificial neural networks were used as pattern recognition techniques. The first heating procedure, applied to a six-sensor array, allowed to classify and to identify five toxic gases (CO, NH3, H2S, C2H2 and NO, each gas concentration was 100 ppm). Moreover, the quantification of gas in binary mixtures was satisfactory, with a RMSEPr value of about 10 %. The second heating procedure, applied to a four-sensor array, allowed to identify three reducing gases (CO, C2H2, and H2S) with concentrations varying from 25 ppm to 100 ppm.
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Contributor : Kieu An Ngo <>
Submitted on : Tuesday, December 12, 2006 - 3:21:30 PM
Last modification on : Thursday, March 15, 2018 - 4:56:03 PM
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  • HAL Id : tel-00119934, version 1



Kieu Ngo. Etude d'un système multicapteur pour la détection sélective des gaz. Micro et nanotechnologies/Microélectronique. Université de droit, d'économie et des sciences - Aix-Marseille III, 2006. Français. ⟨tel-00119934⟩



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