化工学报2019，Vol.70Issue(2)：460-466,7.DOI:10.11949/j.issn.0438⁃1157.20181363
基于多源数据融合的化工园区危险态势感知
Danger situation awareness of chemical industry park based on multiple source data fusion
窦珊 1张广宇 2熊智华 1王焕钢1
作者信息
- 1. 清华大学自动化系,北京100084
- 2. 浙江航天恒嘉数据科技有限公司,浙江嘉兴314201
- 折叠
摘要
Abstract
There are many safety threats in the chemical industry park, such as dangerous goods storage tanks and transport vehicles. The danger situation in the park need to be sensed in real time and potential safety threats must be discovered and eliminated in time. The traditional method relies on a single data source such as real-time monitoring of dangerous goods storage tanks for hazard identification, which is difficult to meet the current needs of the chemical park for safety status assessment. From the point of view of big data analysis, this paper integrates the data of dangerous goods storage tank sensors, dangerous goods transportation(DGT) and geographic information in the chemical park. Based on the characteristics of Gaussian diffusion of dangerous goods leakage, a multi-source heterogeneous data fusion method is proposed. The danger situation identification method realizes the dangerous situation awareness of the park and displays in real time the potential dangerous areas in the entire chemical park. Combined with the actual data of a chemical park, the effectiveness of the proposed method is verified.关键词
数据融合/危险识别/马氏距离/数值分析/安全/集成Key words
data fusion/ hazard identification/ Mahalanobis distance/ numerical analysis/ safety/ integration分类
信息技术与安全科学引用本文复制引用
窦珊,张广宇,熊智华,王焕钢..基于多源数据融合的化工园区危险态势感知[J].化工学报,2019,70(2):460-466,7.
