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Tomographic reconstruction of soil gas distribution from multiple gas sources based on sparse sampling

  • A monitoring method is introduced that creates twodimensional (2D) maps of the soil gas distribution. The method combines linear gas sensing technology for in-situ monitoring of gases in soil with the mapping capabilities of Computed Tomography (CT) to reconstruct spatial and temporal resolved gas distribution maps. A weighted iterative algebraic reconstruction method based on Maximum Likelihood with Expectation Maximization (MLEM) in combination with a source-by-source reconstruction approach is introduced that works with a sparse setup of orthogonally-aligned linear gas sensors. The reconstruction method successfully reduces artifact production, especially when multiple gas sources are present, allowing the discrimination between true and non-existing so-called ghost source locations. Experimental validation by controlled field experiments indicates the high potential of the proposed method for rapid gas leak localization and quantification with respect to Pipeline or underground gasA monitoring method is introduced that creates twodimensional (2D) maps of the soil gas distribution. The method combines linear gas sensing technology for in-situ monitoring of gases in soil with the mapping capabilities of Computed Tomography (CT) to reconstruct spatial and temporal resolved gas distribution maps. A weighted iterative algebraic reconstruction method based on Maximum Likelihood with Expectation Maximization (MLEM) in combination with a source-by-source reconstruction approach is introduced that works with a sparse setup of orthogonally-aligned linear gas sensors. The reconstruction method successfully reduces artifact production, especially when multiple gas sources are present, allowing the discrimination between true and non-existing so-called ghost source locations. Experimental validation by controlled field experiments indicates the high potential of the proposed method for rapid gas leak localization and quantification with respect to Pipeline or underground gas storage issues.zeige mehrzeige weniger

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Metadaten
Autoren/innen:Patrick P. Neumann, D. Lazik, Matthias Bartholmai
Dokumenttyp:Zeitschriftenartikel
Veröffentlichungsform:Verlagsliteratur
Sprache:Englisch
Titel des übergeordneten Werkes (Englisch):IEEE Sensors Journal
Jahr der Erstveröffentlichung:2016
Organisationseinheit der BAM:8 Zerstörungsfreie Prüfung
8 Zerstörungsfreie Prüfung / 8.1 Sensorik, mess- und prüftechnische Verfahren
Herausgeber (Institution):IEEE
Verlag:IEEE - Inst. Electrical Electronics Engineers Inc
Verlagsort:Hoes Lane, NJ, USA
Jahrgang/Band:16
Ausgabe/Heft:11
Erste Seite:4501
Letzte Seite:4508
DDC-Klassifikation:Naturwissenschaften und Mathematik / Chemie / Analytische Chemie
Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Angewandte Physik
Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Sanitär- und Kommunaltechnik; Umwelttechnik
Freie Schlagwörter:Computed tomography; Discrimination of multiple gas sources; Distributed linear sensor; Gas distribution mapping and gas source localization; Gas storage areas; Membrane-based gas sensing; Subsurface monitoring
Themenfelder/Aktivitätsfelder der BAM:Energie
Energie / Energiespeicherung
Umwelt
Umwelt / Umweltschadstoffe
Analytical Sciences
Analytical Sciences / Sensorik
DOI:https://doi.org/10.1109/JSEN.2016.2545103
URL:http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS&DestLinkType=FullRecord;UT=WOS:000375563700063
ISSN:1530-437X
Verfügbarkeit des Volltexts:Volltext-PDF im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:26.05.2016
Referierte Publikation:Ja
Datum der Eintragung als referierte Publikation:02.06.2016