矿井“智慧安监”系统架构设计及实现探究  

Design and Implementation Exploration of the"Intelligent Safety Supervision"System Architecture for Mines

作　　者：郭曦浩 Guo Xihao(Zhangcun Coal Mine of Shanxi Lu'an Environmental Protection Energy Development Co.,Ltd.,Shanxi,046031)

机构地区：[1]山西潞安环保能源开发股份有限公司漳村煤矿,山西046031

出　　处：《当代化工研究》2024年第23期194-196,共3页Modern Chemical Research

摘　　要：针对煤矿现用的视频监控系统结合人工检查的传统安全监查模式存在需人工肉眼识别隐患,耗费人员多、效率低、易出现检查漏洞的问题,为实现煤矿安全隐患的自动识别与预警,基于煤矿安全监查系统研究现状,结合煤矿智能化发展对安监工作提出的新要求,设计了煤矿“智慧安监”系统,介绍了该系统的主要功能,设计了“智慧安监”系统的主要架构,通过综合应用深度学习技术。云计算技术及物联网技术,可自动识别分析监控视频中存在的不安全行为,实现24小时智能监管,减轻了监管人员劳动强度,全面准确地识别了安全隐患,消除了因人为因素引发的漏报错报现象,更好地保障了矿井安全生产。In response to the traditional safety inspection model of coal mine,which combines video surveillance systems with manual inspection,and the problems of needing manual human eye recognition of hazards,high personnel costs,low efficiency,and easy occurrence of inspection gaps,in order to achieve automatic identification and early warning of safety hazards,based on the current research status of coal mine safety inspection systems and the new requirements for safety supervision work put forward by the intelligent development of coal mine,a coal mine"smart safety supervision"system was designed.The paper introduces the main functions of the system and designs the main architecture of the"smart safety supervision"system by integrating deep learning technology,cloud computing technology,and Internet of Things(IoT)technology.It can automatically identify and analyze unsafe behaviors in video surveillance,achieve 24-hour intelligent supervision,reduce the labor intensity of supervisors,accurately identify safety hazards,eliminate the phenomenon of false reporting and underreporting caused by human factors,and better ensure the safe production of coal mine.

关 键 词：安全监控 云计算 物联网 安全隐患 识别 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]