Aufsatz![](/themes/Mirage2/images/Open_Access_logo_PLoS_transparent.svg)
An airborne measurement system to detect, locate, and quantify methane emissions with attitude-based wind speed estimation
Abstract
An airborne measurement system with an onboard computer for data processing and recording that does not require constant radio communication for inspection and maintenance is presented. It detects, locates, and quantifies methane leaks using a gimbal-mounted tunable diode laser absorption spectroscopy (TDLAS) sensor. A polynomial regression model that correlates wind speed with drone attitude is presented and compared to measurements made with a 3D anemometer at varying wind speeds. The quantification of methane emissions was evaluated with the system, both in a laboratory setup and at an open-area test site.
Citation
In: Journal of Sensors and Sensor Systems Volume 13 / Issue 2 (2024-07-29) , S. 211-218 ; eissn:2194-878XSponsorship
Gefördert durch den Publikationsfonds der Universität KasselCitation
@article{doi:10.17170/kobra-2024081610681,
author={Kistner, Lars and Schmoll, Robert and Kroll, Andreas},
title={An airborne measurement system to detect, locate, and quantify methane emissions with attitude-based wind speed estimation},
journal={Journal of Sensors and Sensor Systems},
year={2024}
}
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2024-08-22T11:06:12Z 2024-08-22T11:06:12Z 2024-07-29 doi:10.17170/kobra-2024081610681 http://hdl.handle.net/123456789/15977 Gefördert durch den Publikationsfonds der Universität Kassel eng Namensnennung 4.0 International http://creativecommons.org/licenses/by/4.0/ 600 620 An airborne measurement system to detect, locate, and quantify methane emissions with attitude-based wind speed estimation Aufsatz An airborne measurement system with an onboard computer for data processing and recording that does not require constant radio communication for inspection and maintenance is presented. It detects, locates, and quantifies methane leaks using a gimbal-mounted tunable diode laser absorption spectroscopy (TDLAS) sensor. A polynomial regression model that correlates wind speed with drone attitude is presented and compared to measurements made with a 3D anemometer at varying wind speeds. The quantification of methane emissions was evaluated with the system, both in a laboratory setup and at an open-area test site. open access Kistner, Lars Schmoll, Robert Kroll, Andreas doi:10.5194/jsss-13-211-2024 grant no. 35407/01 Messsystem Erkennung Methanemission Flugkörper publishedVersion eissn:2194-878X Issue 2 Journal of Sensors and Sensor Systems 211-218 Volume 13 false
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