Abstract: In the petrochemical process, a risk monitoring and early warning system for hazardous chemicals is designed based on CPS technology to solve the problems of monitoring, identification and prediction of major hazard sources of hazardous chemicals. The system is divided into three layers: physical layer, network layer and decision layer. At the physical layer, the front⁃end hazardous chemicals data collection, data transmission and local storage are completed, and the data are classified and transmitted to the cloud server in real time. The data passes through the network layer and is identified by the decision⁃making layer for major hazard sources and early warning for hidden dangers of hazardous chemicals. Finally, the whole data is displayed. Genetic algorithm and neural network algorithm are used in the decision⁃making level for risk assessment of major hazard sources. Simulation experiments show that this method can accurately complete the risk assessment of major hazard sources of hazardous chemicals. In the laboratory, the remote monitoring and early warning system for hazardous chemicals based on CPS is proved to have the capability of hazard source identification and risk hazard prediction through actual verification.

Key words: Cyber?physical system, Hazardous chemicals, Data collection, Risk estimation, Risk identification

摘要： 在石油化工过程，采用CPS技术针对危险化学品重大危险源监测辨识预估等问题，设计了一种危险化学品风险监控预警系统。该系统分为物理层、网络层和决策层。在物理层完成前端危险化学品数据采集、数据传输和数据的本地存储，实时将数据分类传送到云端服务器。数据经过网络层由决策层进行重大危险源辨识和危险化学品隐患风险预警，最后对整体进行显示。在决策层采用遗传算法与神经网络算法对重大危险源进行风险评价。结果表明，该方法可以准确完成危险化学品重大危险源风险评价，验证了基于CPS危险化学品远程监控预警系统具备危险源识别及风险隐患预估的能力。

关键词: 信息物理系统, 危险化学品, 数据采集, 风险预估, 风险辨识