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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