化工储罐群安全监测系统的设计与风险预警模型构建

Design of Safety Monitoring System and Risk Early Warning Model for Chemical Storage Tank Group

摘要

化工储罐群作为危险化学品储运的关键设施，其安全水平直接影响企业运行与环境安全。近年来泄漏、爆炸事故频发，暴露出监测滞后与预警不足等问题。本文基于储罐群风险特征，构建融合多源传感信息的智能安全监测系统，结合边缘计算与大数据分析实现实时感知与动态预警。系统通过参数采集、状态识别与风险模型计算，实现储罐全生命周期监控，并设计三层系统架构与融合模糊层次分析—贝叶斯网络的风险评估模型。实验表明，系统预警准确率达93.7%，显著提升监测精度与响应速度，为化工储罐群安全管理提供可推广的智能化路径。

Abstract

As a key facility for the storage and transportation of hazardous chemicals, the safety level of chemical storage tank groups directly affects enterprise operations and environmental safety. In recent years, frequent leakage and explosion accidents have exposed issues such as lagging monitoring and insufficient early warning. Based on the risk characteristics of storage tank groups, this paper constructs an intelligent safety monitoring system that integrates multi-source sensor information, combining edge computing and big data analysis to achieve real-time perception and dynamic early warning. The system realizes full lifecycle monitoring of storage tanks through parameter acquisition, status recognition, and risk model calculation, and designs a three-layer system architecture with a risk assessment model integrating fuzzy analytic hierarchy process and Bayesian network. Experiments show that the system’s early warning accuracy reaches 93.7%, significantly improving monitoring precision and response speed, providing a scalable intelligent approach for the safety management of chemical storage tank groups.

关键词

化工储罐群 / 安全监测 / 风险预警 / 多源数据融合 / 智能感知

Key words

chemical storage tank cluster / safety monitoring / risk early warning / multi-source data fusion / intelligent sensing

参考文献

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