流程行业智能工厂多源、多尺度、多时空安全风险耦合机制数据集

流程行业智能工厂多源、多尺度、多时空安全风险耦合机制数据集基于流程行业智能工厂信息物理系统，涵盖攻击安全、故障安全、失效安全风险动态演化过程中的耦合机制。数据集整合催化裂化装置的设备清单与技术规格，柴油加氢装置的设备清单与技术规格、工艺报警日志以及催化装置循环油浆系统汽水分离器的设备清单与技术规格、控制结构、模糊综合评估数据等数据，包括DCS/SCADA系统实时数据（OPC UA协议导出）及EAM系统维护日志等，经结构化验证与跨源对齐形成数据集。在此基础上，开发了基于复杂网络动态特性的集总风险辨识与评估方法，构建了故障/失效与信息攻击安全风险的动力学关联机理及其耦合机制特征表达。采用多源交叉验证、人工筛选清洗及跨源对齐技术实现质量控制，数据存储为结构化Excel表格，具备高兼容性。数据集为流程行业智能工厂跨域风险量化评估与动态防护优化提供理论支持，推动智能工厂信息物理系统多域协同风险防控的发展。Dataset of Multi-source, Multi-scale, Multi-spatiotemporal Security Risk Coupling Mechanisms for Intelligent Plants in the Process Industry. Based on the cyber-physical systems of intelligent plants in the process industry, this dataset covers the coupling mechanisms during the dynamic evolution of attack security, fault security and failure security risks. The dataset integrates multiple types of data, including equipment lists and technical specifications of fluid catalytic cracking units and diesel hydrotreating units, process alarm logs, equipment lists, technical specifications, control structures and fuzzy comprehensive evaluation data of the steam-water separator in the circulating oil slurry system of the catalytic unit, real-time data from DCS/SCADA systems (exported via OPC UA protocol), maintenance logs of the EAM system, etc. It is formed into a standardized dataset through structured verification and cross-source alignment. On this basis, a lumped risk identification and evaluation method based on the dynamic characteristics of complex networks has been developed, and the dynamic correlation mechanism between fault/failure and cyber-attack security risks as well as the characteristic expression of their coupling mechanisms have been constructed. Quality control is realized through multi-source cross-validation, manual screening and cleaning, and cross-source alignment technologies. The data is stored in structured Excel tables with high compatibility. This dataset provides theoretical support for cross-domain risk quantitative assessment and dynamic protection optimization of intelligent plants in the process industry, and promotes the development of multi-domain collaborative risk prevention and control for cyber-physical systems of intelligent plants.

搜集汇总

背景与挑战

背景概述

该数据集基于流程行业智能工厂信息物理系统，聚焦于攻击、故障、失效等多源安全风险的动态演化耦合机制。它整合了催化裂化、柴油加氢等装置的设备清单、技术规格、工艺日志等多尺度数据，并经过结构化验证与跨源对齐处理。数据集旨在为流程行业智能工厂的跨域风险量化评估与动态防护优化提供理论支持。