Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Localization and Quantification of Emission Rate
Abstract
:1. Introduction
2. Datasets and Procedures
3. Algorithm Development
3.1. Localization Algorithms
3.2. Quantification Algorithms
3.3. Detection Algorithm
4. Algorithm Performance
4.1. Leak Localization
4.2. Leak Detection and Quantification
4.3. Component Sensitivity and Uncertainty Analyses
5. Discussion
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Golston, L.M.; Aubut, N.F.; Frish, M.B.; Yang, S.; Talbot, R.W.; Gretencord, C.; McSpiritt, J.; Zondlo, M.A. Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Localization and Quantification of Emission Rate. Atmosphere 2018, 9, 333. https://doi.org/10.3390/atmos9090333
Golston LM, Aubut NF, Frish MB, Yang S, Talbot RW, Gretencord C, McSpiritt J, Zondlo MA. Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Localization and Quantification of Emission Rate. Atmosphere. 2018; 9(9):333. https://doi.org/10.3390/atmos9090333
Chicago/Turabian StyleGolston, Levi M., Nicholas F. Aubut, Michael B. Frish, Shuting Yang, Robert W. Talbot, Christopher Gretencord, James McSpiritt, and Mark A. Zondlo. 2018. "Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Localization and Quantification of Emission Rate" Atmosphere 9, no. 9: 333. https://doi.org/10.3390/atmos9090333