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铁路现场安全监督管理系统设计研究 被引量:3

Research on Design of Railway Site Safety Supervision and Management System
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摘要 加强铁路现场安全监督管理,提升隐患排查的深度、广度,强化隐患治理的针对性、协同性和彻底性,及时发现隐蔽性、倾向性问题,对预防事故发生具有重要的作用。在阐述铁路现场安全监督管理系统设计背景的基础上,针对现场检查信息的采集、数据的多维度统计分析、隐患的动态跟踪、管理人员履职、安全预警等设计目标,对系统的工作流程、物理架构、逻辑架构进行了设计,研究数据深度挖掘与过程管控、安全预警等功能的工作机理,提出相应的技术措施。系统实现对管理人员履职情况的监督,薄弱环节的识别、预警与控制功能,可为铁路现场安全管控提供有力的技防支撑,不断完善隐患排查和风险防范机制,提升安全管理工作的效率、信息化水平和对现场安全的整体管控力。 Strengthening the railway site safety supervision and management, improving the depth and breadth of potential danger investigation, enhancing the pertinence, coordination, and thoroughness of potential danger management, and timely finding concealed and inclined problems play an important role in preventing accidents. On the basis of introducing the design background of the railway site safety supervision and management system, this paper designed the system’s workflow, physical architecture, and logical architecture with the collection of on-site inspection information,multi-dimensional statistical analysis of data, dynamic tracking of potential danger, management personnel performance,safety early warning, etc. as the design goals. The paper studied the working mechanisms of data deep mining, process control, safety early warning, and other functions and proposed corresponding technical measures. The system realizes the supervision of site management staff and the identification, early warning, and control of weak links, which can provide powerful technical support for railway site safety management and control, continuously complete potential danger investigation and risk prevention mechanisms, and improve the efficiency and informatization level of safety management and the overall control of railway site safety.
作者 赵亚龙 ZHAO Yalong(Batuta Station Area,Guoneng Baoshen Railway Co.,Ltd.,Ordos 017000,Inner Mongolia,China)
出处 《铁道运输与经济》 北大核心 2023年第1期39-46,共8页 Railway Transport and Economy
基金 国能包神铁路集团有限责任公司科技创新课题(TZ2020120)。
关键词 铁路安全 信息采集 履职管理 薄弱环节识别 预警 统计分析 Railway Safety Information Collection Performance Management Weak Link Identification Early Warning Statistical Analysis
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