边缘计算驱动的瓦斯灾害智能感知方法研究
Research on intelligent sensing method of gas disaster driven by edge computing
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摘要: 针对回采面瓦斯单点监测模式存在较多监测盲区及无法展现瓦斯流场分布状态的问题，基于边缘计算技术提出了构建回采面瓦斯体积分数场并视觉显示瓦斯流场以及监测预警瓦斯涌出异常的方法，该方法革新了瓦斯传统监测模式，用面域监测取代单点监测，边缘计算网关替代通用监控分站，实现回采面瓦斯的全覆盖监测及井下就地构建数据场、云图展示和异常起伏捕捉，具体思路如下：通过现场实测数据获得回采面瓦斯“台阶上升”和“渐变上升”的分布特征，据此设计了瓦斯全覆盖的监测方案，借助新型MEMS瓦斯传感器完成瓦斯的全覆盖监测布置系统；监测数据通过无线或有线方式传输至边缘计算网关；边缘计算网关安设在回采巷道内，内嵌数据处理模型、单点瓦斯体积分数异常波动判别模型，数据处理模型构建瓦斯数字场、形成瓦斯动态云图，单点瓦斯体积分数异常判别模型对单点瓦斯体积分数异常起伏进行判断，分区判定模式完成回采面瓦斯异常起伏行为捕捉；最终实现瓦斯体积分数场云图的宏观展示和异常起伏的微观捕捉。Abstract: Aiming at the problems of more blind monitoring areas and unable to show the distribution of gas flow field in single point monitoring mode of gas in mining face, based on edge computing technology, a method of constructing gas concentration field in mining face, visual display of gas flow field and monitoring and early warning of abnormal gas emission is proposed. The platform revolutionized the traditional methane monitoring model, replaced single-point monitoring with area monitoring, replaced methane substations with edge computing gateways, and realized global monitoring of methane in coal mining faces, built methane data fields underground, displayed methane cloud diagrams, and captured methane emission abnormally. The specific ideas are as follows: the distribution characteristics of “step rise” and “gradual rise” of methane in mining face are obtained by field measured data. Based on this, a full coverage monitoring scheme of methane is designed, and the full coverage monitoring layout system of methane is completed by using a new MEMS methane sensor; the monitoring data are transmitted to the edge computing gateway by wireless or wired means; edge computing gateway is located in mining roadway, embedded data processing model, single point methane concentration abnormal jump recognition model and periodic abnormal fluctuation discrimination model. The data processing model to build methane digital field, methane dynamic cloud diagrams, the jump model of single point methane concentration anomaly are used to judge the fluctuation of single point methane concentration anomaly, the discrimination by region mode to complete the mining face methane abnormal fluctuation behavior capture. Finally, the macroscopic display of methane concentration field cloud diagram and microscopic capture of abnormal fluctuation of methane concentration are realized.
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