Implementation of a UAV-sensory-system-based hazard source estimation in a chemical plant cluster

2019 3rd International Conference on Energy and Environmental Science

能源学;生态环境科学

Li, Dan^1 ; Chen, Feiran^1 ; Wang, Yiping^2 ; Wang, Xiaodong^2

Graduate School, National University of Defense Technology, 109 Deya Road, Changsha, Hunan

410073, China^1

Naval 902 Factory, Shanghai

200000, China^2

关键词: Bayesian inference;    Chemical production;    Leakage and dispersions;    Monitoring system;    Safety monitoring;    Sensory system;    Source estimation;    Source tracing;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/291/1/012043/pdf
DOI  :  10.1088/1755-1315/291/1/012043

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Since there has been growing concern about the damage that atmospheric leakage and dispersion accidents may have done to human beings, researchers are dedicated to study effective and feasible source estimation methods in chemical plant clusters. In this paper, the safety monitoring of chemical production process is conducted via an unmanned aerial vehicle (UAV) monitoring system. Based on the observed data from this system, a source estimation method incorporating Bayesian inference and Particle Swarm Optimization (PSO) is proposed. Furthermore, the method is extended to discuss the source tracing algorithm using game theory in the UAV system. Finally, a practical case study is carried out to verify the feasibility and credibility of the proposed method. Results show that the method and system are helpful for safety monitoring and risk assessment in a chemical plant cluster.