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Experimental Validation of the Cone-Shaped Remote Gas Sensor Model
Bundesanstalt für Materialforschung und -prüfung (BAM) Berlin, Germany. (AASS MRO Lab)
Bundesanstalt für Materialforschung und -prüfung (BAM) Berlin, Germany.
Bundesanstalt für Materialforschung und -prüfung (BAM) Berlin, Germany.
Bundesanstalt für Materialforschung und -prüfung (BAM) Berlin, Germany.
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2019 (English)In: 2019 IEEE SENSORS, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Remote gas sensors mounted on mobile robotsenable the mapping of gas distributions in large or hardlyaccessible areas. A challenging task, however, is the generation ofthree-dimensional distribution maps from the gas measurements.Suitable reconstruction algorithms can be adapted, for instance,from the field of computed tomography (CT), but both theirperformance and strategies for selecting optimal measuring posesmust be evaluated. For this purpose simulations are used, since, incontrast to field tests, they allow repeatable conditions. Althoughseveral simulation tools exist, they lack realistic models of remotegas sensors. Recently, we introduced a model for a Tunable DiodeLaser Absorption Spectroscopy (TDLAS) gas sensor taking intoaccount the conical shape of its laser beam. However, the novelmodel has not yet been validated with experiments. In this paperwe compare our model with a real sensor device and show thatthe assumptions made hold.

Place, publisher, year, edition, pages
2019.
Keywords [en]
Remote gas sensor model, TDLAS, gas dispersion simulation
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-79742DOI: 10.1109/SENSORS43011.2019.8956613Scopus ID: 2-s2.0-85078700634ISBN: 978-1-7281-1634-1 (electronic)OAI: oai:DiVA.org:oru-79742DiVA, id: diva2:1391191
Conference
IEEE Sensors 2019, Montreal, Canada, October 27 - 30, 2019
Available from: 2020-02-03 Created: 2020-02-03 Last updated: 2020-02-07Bibliographically approved

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Experimental Validation of the Cone-Shaped Remote Gas Sensor Model(1265 kB)56 downloads
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Hüllmann, DinoLilienthal, Achim J.

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