中国安全科学学报 ›› 2026, Vol. 36 ›› Issue (8): 102-107.doi: 10.16265/j.cnki.issn1003-3033.2026.08.0738

• 安全技术与工程 • 上一篇    下一篇

基于五流协同理论的智能安全管理及风险防控机制

徐波1(), 张建文2,3,**(), 韩毅1, 及燕铭1, 马世海1   

  1. 1 中国安全生产科学研究院, 北京 100012
    2 北京化工大学 安全工程系, 北京 100029
    3 北京化工大学 化学工程学院, 北京 100029
  • 收稿日期:2026-03-02 修回日期:2026-05-24 出版日期:2026-08-28
  • 通信作者:
    **张建文(1969—),男,山西夏县人,博士,教授,主要从事化学工程与化工安全方面的研究。E-mail:
  • 作者简介:

    徐波 (1975—),男,陕西山阳人,博士,高级工程师,主要从事安全生产及应急管理等方面的研究。E-mail:

    韩毅 高级工程师

    马世海 教授级高级工程师

  • 基金资助:
    “十四五”国家重点研发计划项目(2021YFB3301100); “十四五”国家重点研发计划项目(2023YFC3011704)

Intelligent safety management and risk prevention-control mechanism based on Five-Flow Synergy Theory

Xu Bo1(), Zhang Jianwen2,3,**(), Han Yi1, Ji Yanming1, Ma Shihai1   

  1. 1 China Academy of Safety Science and Technology, Beijing 100012, China
    2 Department of Safety Engineering, Beijing University of Chemical Technology, Beijing 100029, China
    3 College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, China
  • Received:2026-03-02 Revised:2026-05-24 Published:2026-08-28

摘要:

为弥补现有智能安全研究重实操、轻机制的理论短板,完善智能安全领域底层理论体系,提出基于五流协同理论的智能安全管理及风险防控机制。通过梳理物质流、能量流、数字流、信息流、控制流的内在协同逻辑,揭示单流异常、多流耦合失衡的事故演化机制,提出针对五流事故致因特征的靶向防控机制;搭建包含“感知层-网络层-平台层-执行层”的4层技术架构与“云-边-端”三级协同架构;建立兼具数据贯通、责任追溯、跨域联动特征的五流协同管理机制,形成“全域感知-动态评估-智能预警-协同控制”的全链条主动风险防控体系;并结合化工生产、应急救援等典型工业场景完成模式有效性验证。研究结果表明:基于五流协同理论构建的安全生产管理模式,可合理解释新型工业安全事故成因,支撑风险全域感知、智能研判与闭环处置。

关键词: 五流协同理论, 智能安全管理, 风险防控, 工业互联网, 安全生产

Abstract:

To fill the theoretical deficiency of emphasizing practical operation while ignoring underlying mechanisms in existing intelligent safety research and improve the fundamental theoretical system of intelligent safety, proposes an intelligent safety management and risk prevention and control mechanism based on Five-Flow Synergy Theory was proposed. By clarifying the internal collaborative logic of material flow, energy flow, digital flow, information flow and control flow, this study revealed the accident evolution mechanism induced by single flow abnormality and multi-flow coupling imbalance. Targeted prevention and control mechanisms adapted to the five-flow accident causation characteristics were proposed. A four-layer technical architecture consisting of the perception layer, network layer, platform layer and execution layer, as well as a cloud-edge-terminal three-level collaborative architecture were established. Furthermore, a five-flow collaborative management mechanism featuring data penetration, responsibility traceability and cross-domain linkage was constructed, forming a full-chain active risk prevention and control system with full-domain perception, dynamic assessment, intelligent early warning and collaborative control. The effectiveness of the proposed model was verified through typical industrial scenarios including chemical production and emergency rescue. The research results indicate that, the safety management model constructed based on the Five-Flow Synergy Theory can reasonably explain the causes of new-type industrial safety accidents, support full-domain risk perception, intelligent analysis and judgment as well as closed-loop disposal, and effectively enhance safety resilience and prevention and control capabilities.

Key words: Five-Flow Synergy Theory, intelligent safety management, risk prevention and control, industrial internet, work safety

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