段金红, 马新根, 贺永强, 张笃学, 巩永春, 付康国, 郭卫洪. 基于全流程可追溯的煤矿安全智慧管控云平台[J]. 煤矿安全, 2023, 54(6): 223-228.
    引用本文: 段金红, 马新根, 贺永强, 张笃学, 巩永春, 付康国, 郭卫洪. 基于全流程可追溯的煤矿安全智慧管控云平台[J]. 煤矿安全, 2023, 54(6): 223-228.
    Intelligent management and control cloud platform for coal mine safety based on full process traceability[J]. Safety in Coal Mines, 2023, 54(6): 223-228.
    Citation: Intelligent management and control cloud platform for coal mine safety based on full process traceability[J]. Safety in Coal Mines, 2023, 54(6): 223-228.

    基于全流程可追溯的煤矿安全智慧管控云平台

    Intelligent management and control cloud platform for coal mine safety based on full process traceability

    • 摘要: 为有效解决现有煤炭行业各系统单独建设、多系统数据缺乏共享、智能分析及数据挖掘利用率低等问题,利用物联网、大数据、人工智能等信息技术,在深度融合煤矿安全管理业务的基础上,提出全流程可追溯的煤矿安全智慧管控云平台建设方案;重点分析了风险管控、隐患排查、班组任务处理、违章纠违等业务流程;平台通过数据中心实现多源异构监测数据的存储、整合及分析,将煤矿安全管理中涉及的9个子系统集成于安全智慧管控平台中,利用数据共享一张图进行协同管控与数据有效分析展示。应用结果表明:平台实现了煤矿数据融合、协同控制、业务联动与决策,在提高安全管控效率、缩减管控成本、最大化企业利益方面有较好效果。

       

      Abstract: In order to effectively solve the problems of independent construction of various systems in the existing coal industry, lack of sharing of multi-system data, low utilization of intelligent analysis and data mining, this paper uses the Internet of Things, big data, artificial intelligence and other information technologies, and on the basis of in-depth integration of coal mine safety management business, we proposed the construction scheme of the whole process traceable coal mine safety intelligent management and control cloud platform, focusing on the analysis of risk management and control, hidden danger trouble shooting, team task processing business processes such as violation correction. The platform realizes the storage, integration and analysis of multi-source heterogeneous monitoring data through the data center, integrates the nine subsystems involved in coal mine safety management into the safety intelligent management and control platform, and uses the data to share a chart for collaborative management and control and effective analysis and display of data. The application results show that the platform has realized coalmine data fusion, collaborative control, business linkage and decision-making, and has a good effect in improving safety control efficiency, reducing control costs and maximizing enterprise interests.

       

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