Characteristics of typical safety patrol scenarios and reliability analysis of patrol inspection in coal mines
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摘要:
从《煤矿安全规程》对人工巡检的具体要求和现场安全巡检的实际需求入手，针对当前煤矿人工巡检工作自动化、信息化程度低、巡检结果数据可靠性不高的问题，提出了通过信息化手段和智能化研判对人工巡检进行辅助的方式，来提高安全巡检效率和典型场景巡检数据可靠性问题。通过对人工测风场景、井下瓦斯巡检场景和甲烷传感器标校场景的特征分析，提出了安全巡检信息化系统的架构；对应3种典型的巡检场景，利用精确人员定位系统、安全监控系统和安全巡检信息化系统本身的数据分别建立了巡检数据可靠性研判模型。以综采工作面甲烷传感器标校数据为例，对进风巷、上隅角、工作面和回风巷4个甲烷传感器标校数据的可靠性进行了研判，分析结果与现场实际情况一致，说明该方法能够在一定范围内对安全巡检的有效性和可信度进行提高。
Abstract:Starting from the specific requirements of manual patrol inspection and the actual requirements of on-site safety patrol inspection in the Code for Coal Mine Safety, in view of the low degree of automation and informatization of the current coal mine safety inspection, the reliability of the inspection results is untrusted. This paper proposes a supplementary method of artificial patrol inspection, by means of information technology and intelligent research and decision to improve the efficiency of security patrol inspection and the reliability of patrol data in typical scenarios. Based on the analysis of the characteristics of artificial wind patrol scene, underground gas patrol scene and methane sensor calibration patrol scene, the architecture of safety patrol information system is proposed. Corresponding to three typical patrol scenarios, the reliability research model of patrol data is established by using the data of precise personnel positioning system, security monitoring system and security patrol information system. Taking the methane sensor calibration patrol data of the fully mechanized mining face as an example, the reliability of the calibration data of the four methane sensors in the air inlet, upper corner, working face and air return roadway is evaluated. The results of analysis are highly consistent with the actual situation in the field, which can improve the validity and reliability of security patrol to a certain extent.
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图 2 人工测风场景巡检数据可靠性判断逻辑
Figure 2. Reliability judgment logic of patrol inspection data in manual wind measurement scenario
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图 3 瓦斯巡检场景数据可靠性判断逻辑
Figure 3. Logic for judging the reliability of gas patrol scene data
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图 4 甲烷传感器标校场景数据可靠性判断逻辑
Figure 4. Methane sensor calibration scene data reliability judgment logic
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图 5 某综采工作面传感器布置示意图
Figure 5. Schematic diagram of sensor layout for a fully mechanized mining face
表 1 综采工作面甲烷传感器标校巡检数据表
Table 1 Data table of methane sensor calibration and inspection in fully mechanized mining face
序号 传感器
名称标校开
始时刻标校完
成时刻最大体积分
数值/%最大体积分数
持续时间/s1 进风巷甲烷 9：01：10 9：07：15 2.0 30 2 上隅角甲烷 9：15：20 9：18：10 2.0 95 3 工作面甲烷 9：25：30 9：32：20 2.0 95 4 回风巷甲烷 10：01：10 10：07：10 2.0 110 
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