Safety risks monitoring and warning throughout the full lifecycle of mine air stopping
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摘要: 矿井密闭是分隔生产系统与废弃系统的关键设施，做好全生命周期风险管控对保障安全生产意义重大。基于矿井密闭综合管控技术现状，从静态属性信息管理与动态信息监控2个方面剖析了现有密闭管理模式的不足。提出了密闭全生命周期智能管控的理念，指明基于物联网（IoT）+人工智能（AI）+云平台（CP）的大数据策略与集成云边端架构的密闭安全风险监测预警总体建设路径。应用IoT平台接入密闭单元的数字化监测与联动控制设备，实现密闭全生命周期管控透明化；以密闭信息演化征兆及边缘高效计算为核心，部署移动端、边缘计算机等现场终端，适配密闭服役状态的在线预测与超前预警；在智慧云端，以多源融合信息与数字孪生模型为核心，实时迭代重构分布式矿井密闭的虚拟现实场景及其全生命周期演化特征。分析了密闭环境演化信息的物理−数字驱动模式、密闭感知信息的多源异构数据融合模型、密闭异常边缘检测与分级智能预警、密闭全生命周期应急智能决策与协同防控等关键理论与模型构建方法。设计了基于IoT的密闭全生命周期安全风险监测预警系统的物理与功能架构，研制了现场嵌入式密闭多参数一体化监测传感器及配套的智能化主机，提出了密闭风险的早期感知与监测预警方法，以期实现数字赋能，切实推进智慧矿山建设。Abstract: Mine air stopping is a key facility separating production systems from abandoned ones. Ensuring full lifecycle risk management is of great significance for ensuring safe production. Based on the current status of comprehensive control technology for mine air stopping, the shortcomings of the existing air stopping management mode are analyzed from two aspects: static attribute information management and dynamic information monitoring. The paper puts forward the concept of intelligent management and control in the full lifecycle of air stopping. It indicates the overall construction path of air stopping risk monitoring and early warning based on big data strategy of the Internet of Things (IoT)+Artificial Intelligence (AI)+Cloud Platform (CP), and integrated with cloud-edge architecture. The IoT platform is applied to access digital monitoring and linkage control equipment for air stopping units, achieving transparency in the full lifecycle control of air stopping. The method focuses on the evolution signs of air stopping information and efficient edge computing. It deploys mobile terminals, edge computers and other field terminals to adapt to online prediction and advance warning of air stopping service status. In the smart cloud, the virtual reality scenario of a distributed mine air stopping and its full lifecycle evolution characteristics are reconstructed iteratively in real time with multi-source fused information and digital twin models at the core. The paper analyzes key theories and and model construction methods, including the physical-digital driving mode of evolution information in air stopping environments, the multi-source heterogeneous data fusion model of air stopping perception information, the edge detection and hierarchical intelligent warning of air stopping anomalies, and the emergency intelligent decision-making and collaborative prevention and control throughout the entire lifecycle of air stopping. The physical and functional architecture of an air stopping full lifecycle safety risk monitoring and warning system based on the IoT is designed. The on-site embedded air stopping multi-parameter integrated monitoring sensors and supporting intelligent hosts are developed. The early sensing and monitoring and warning methods for air stopping risks are proposed to achieve digital empowerment and effectively promote the construction of smart mines.
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图 1 煤矿密闭监测气样监测管布置
Figure 1. Layout of gas sample monitoring pipes for air stopping in coal mines
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图 2 煤矿设备巡检系统物理架构
Figure 2. Physical architecture of coal mine equipment inspection system
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图 3 矿井密闭全生命周期安全风险监测预警系统物理架构
Figure 3. Physical architecture of safety risk monitoring and early warning system for the full lifecycle of air stopping
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图 4 矿井密闭全生命周期安全风险监测预警系统功能架构
Figure 4. Functional architecture of safety risk monitoring and early warning system for the full lifecycle of air stopping
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图 5 密闭环境信息感知IoT传感器
Figure 5. IoT sensor for environment information monitoring of air stopping
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图 6 密闭环境信息监测系统主机
Figure 6. Air stopping internal environmentinformation monitoring system host
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图 7 密闭安全风险监测预警系统安装方式
1−监测主机；2−感压管；3−预埋套管；4−多参数一体化传感器；5−航空插头；6−电缆套管（连接杆）；7−管帽；8−矿用防爆电缆。
Figure 7. Installation method of air stopping risk monitoring and warning system
表 1 传感器的主要技术指标
Table 1 Main technical indicators of sensors
参数名称 量程 误差 甲烷体积分数 0～10% ±6% 一氧化碳
体积分数0～0.1% ±5% 氧气体积分数 0～25% ±3% 差压 −1 000～1 000 Pa ±1% 绝对压力 0～2000 hPa ±1% 温度 0～80 ℃ ±0.5 ℃ 
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[1] 赵庆跃. 屡越“红线”连酿惨剧——吉林八宝煤业公司“3·29”特别重大瓦斯爆炸事故案例分析[J]. 吉林劳动保护,2013(8):37-39. ZHAO Qingyue. Repeatedly crossing the "red line" and continuously brewing tragedy-analysis of the case of Jilin Babao Coal Industry Company's "3·29" special major gas explosion accident[J]. Jilin Labour Protection,2013(8):37-39.
[2] 魏军军. 唐阳煤矿230封闭采空区惰化技术研究与应用[D]. 徐州: 中国矿业大学, 2021 WEI Junjun. Research and application of inerting characteristics in 230 closed goaf fire area of Tangyang Coal Mine [D]. Xuzhou: China University of Mining and Technology, 2021.
[3] AQ 1044—2007 矿井密闭防灭火技术规范[S]. AQ 1044-2007 Technical standard of preyention and extinguish of mine fire by air stopping[S].
[4] 滕博,姜福兴,莫自宁,等. 煤矿防爆密闭墙技术标准探讨[J]. 煤炭科学技术,2007,35(2):97-100. DOI: 10.3969/j.issn.0253-2336.2007.02.029 TENG Bo,JIANG Fuxing,MO Zining,et al. Discussion on technical standard of mine flame proof seal dam[J]. Coal Science and Technology,2007,35(2):97-100. DOI: 10.3969/j.issn.0253-2336.2007.02.029
[5] 张建亮,夏志成,周竞洋,等. 密闭空间内三种防爆隔墙的减爆吸能效应分析[J]. 工程力学,2017,34(增刊1):314-319. ZHANG Jianliang,XIA Zhicheng,ZHOU Jingyang,et al. Analysis on the explosion isolation and absorption effect of three kinds of explosion proof walls in airtight space[J]. Engineering Mechanics,2017,34(S1):314-319.
[6] NB/T 10731—2021煤矿井下防水密闭墙设计施工及验收规范[S]. NB/T 10731-2021 Specification for design construction and acceptance of waterproof dam in coal mine[S].
[7] 胡朝辉. 深部矿井采空区防火密闭墙技术应用实践[J]. 煤炭与化工,2022,45(5):111-113. HU Chaohui. Application practice of fire-proof closed wall technology in deep mine goaf[J]. Coal and Chemical Industry,2022,45(5):111-113.
[8] 宋红华,黄玉诚,张博. 深井采空区密闭墙系统构筑原理及应用[J]. 煤矿开采,2015,20(5):6-10. SONG Honghua,HUANG Yucheng,ZHANG Bo. Construction theory and application of sealing wall system against gob in deep mine[J]. Coal Mining Technology,2015,20(5):6-10.
[9] 李瑞群. 大柳塔煤矿各类密闭的设计和施工工艺研究[J]. 陕西煤炭,2016,35(增刊1):24-27. LI Ruiqun. Research on the design and construction technology of closed walls in Daliuta Coal Mine[J]. Shaanxi Coal,2016,35(S1):24-27.
[10] 蒋曙光,李亚东,邹力力,等. 基于气相色谱技术的采空区煤自燃火灾预测预报研究[J]. 工矿自动化,2010,36(6):38-40. JIANG Shuguang,LI Yadong,ZOU Lili,et al. Research of forecasting of spontaneous combustion of coal in mined-out area based on technology of gas chromatography[J]. Industry and Mine Automation,2010,36(6):38-40.
[11] 梁运涛,孙勇,罗海珠,等. 基于小样本的煤层自然发火烷烃气体的光谱分析[J]. 煤炭学报,2015,40(2):371-376. LIANG Yuntao,SUN Yong,LUO Haizhu,et al. Spectral analysis of alkane gases of coal spontaneous combustion with a small quantity sample[J]. Journal of China Coal Society,2015,40(2):371-376.
[12] 安徽理工大学. 一种判定煤矿采空区群密闭墙漏风源、汇装置及方法: 2019100218451[P]. 2019-01-10. Anhui University of Science and Technology. A method for determining the source and sink of air leakage from sealed walls in goaf groups of coal mines: 2019100218451[P]. 2019-01-10.
[13] 山东科技大学. 采空区及密闭空间的气体浓度场三维实时监测系统及方法: 201810204089.1[P]. 2018-03-13. Shandong University of Science and Technology. Three dimensional real-time monitoring system and method for gas concentration field in goaf and enclosed space: 201810204089.1[P]. 2018-03-13.
[14] 吴响,张立,王丹. 基于ZigBee的煤矿采空区环境实时监测系统设计[J]. 煤炭技术,2014,33(4):251-253. WU Xiang,ZHANG Li,WANG Dan. Design of real-time environment monitoring system of coal mine goaf based on ZigBee[J]. Coal Technology,2014,33(4):251-253.
[15] 中煤科工集团重庆研究院有限公司. 一种采空区气体原位监测装置: 202220606803.1[P]. 2022-03-18. CCTEG Chongqing Research Institute. A in-situ monitoring device for gas in goaf: 202220606803.1[P]. 2022-03-18.
[16] 刘旭. 朱集矿“Y”型通风工作面临时密闭墙在线监测系统[C]. 安徽省煤炭学会通风安全专业委员会六届三次学术交流会, 鄂尔多斯, 2012: 148-150. LIU Xu. Online monitoring system for enclosed walls in the "Y" type ventilation working face in Zhuji Mine[C]. The Third Academic Exchange Meeting of the 6th Ventilation Safety Professional Committee of Anhui Coal Association, Ordos, 2012: 148-150.
[17] 胡秋. T企业实物资产全生命周期管理研究[D]. 扬州: 扬州大学, 2022. HU Qiu. The research on physical assets management of company T based on the whole life cycle[D]. Yangzhou: Yangzhou University, 2022.
[18] SANGEETHA R G, HEMANTH C, MARATI N K. Remote electric vehicle battery monitoring & life cycle management system[C]. IEEE 2nd International Conference on Sustainable Energy and Future Electric Transportation, Hyderabad, 2022. DOI: 10.1109/SeFeT55524.2022.9909384.
[19] 何为. 物联网框架下蓄电池全生命周期监控[D]. 北京: 北京交通大学, 2014. HE Wei. Battery lifecycle monitoring under the framework of IoT[D]. Beijing: Beijing Jiaotong University, 2014.
[20] 周军华,杨春霞,谢子萍,等. 基于物联网的医疗设备全生命周期管理系统设计[J]. 中国医学装备,2021,18(5):133-135. ZHOU Junhua,YANG Chunxia,XIE Ziping,et al. Design on whole life-cycle management system of medical equipment based on Internet of things[J]. China Medical Equipment,2021,18(5):133-135.
[21] 深圳市科陆电子科技股份有限公司. 基于物联网技术的输变电设备全生命周期管理系统: 2010106051691[P]. 2010-12-25. Shenzhen CLOU Electronics Co., Ltd. . Life cycle management system of power transmission and transformation equipment based on Internet of things technology: 2010106051691[P]. 2010-12-25.
[22] 徐鹏. 物联网在智能矿山建设中的应用研究[J]. 煤炭技术,2021,40(6):202-204. XU Peng. Study on Internet of things application in intelligent mine construction[J]. Coal Technology,2021,40(6):202-204.
[23] 刘振华,徐绪堪. 基于物联网的煤矿机电设备智能管理平台设计[J]. 工矿自动化,2019,45(4):101-104,108. LIU Zhenhua,XU Xukan. Design of intelligent management platform for coal mine electromechanical equipments based on Internet of things[J]. Industry and Mine Automation,2019,45(4):101-104,108.
[24] 崔希国,韩安. 基于RFID的煤矿设备巡检系统设计[J]. 工矿自动化,2018,44(10):77-80. CUI Xiguo,HAN An. Design of inspection system for coal mine equipments based on RFID[J]. Industry and Mine Automation,2018,44(10):77-80.
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