Abstract
Estimating contaminant source has become increasingly important to hazard assessment and emergency management of air contaminant nowadays. In this paper, a source estimation method is proposed to estimate the location and release rate of source. The theoretical basis of this source estimation method is Bayesian inference using the atmospheric dispersion model, Particle Swarm Optimization (PSO) and the observed data. An improved Gaussian dispersion model is proposed to model the continuous emission source. In order to obtain the observed data, a UAV-based air contaminant sensory system is developed consisting of an aerial platform and a sensory system. An experiment is conducted in a chemical industry park to verify the feasibility and credibility of this UAV-based system. Furthermore, the source estimation method proposed recovers the location and release rate of source with a high accuracy, confirming the effectiveness of the method.
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Acknowledgements
This study is supported by National Key Research & Development (R&D) Plan under Grant No. 2017YFC0803300 and the National Natural Science Foundation of China under Grant Nos. 71673292, 61503402 and Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion and Shanghai Special Foundation of Software and Integrated Circuit under Grant No. 150312.
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Wang, R., Chen, B., Qiu, S., Zhu, Z., Qiu, X. (2017). Hazard Source Estimation Based on the Integration of Atmospheric Dispersion Simulation and UAV Sensory System. In: Mohamed Ali, M., Wahid, H., Mohd Subha, N., Sahlan, S., Md. Yunus, M., Wahap, A. (eds) Modeling, Design and Simulation of Systems. AsiaSim 2017. Communications in Computer and Information Science, vol 751. Springer, Singapore. https://doi.org/10.1007/978-981-10-6463-0_42
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DOI: https://doi.org/10.1007/978-981-10-6463-0_42
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