魏连江, 胡青伟, 梁伟, 任飞. 基于K线图理论的瓦斯异常模式诊断研究[J]. 煤矿安全, 2019, 50(6): 24-27,31.
    引用本文: 魏连江, 胡青伟, 梁伟, 任飞. 基于K线图理论的瓦斯异常模式诊断研究[J]. 煤矿安全, 2019, 50(6): 24-27,31.
    WEI Lianjiang, HU Qingwei, LIANG Wei, REN Fei. Research on Gas Abnormal Mode Diagnosis Based on K-line Theory[J]. Safety in Coal Mines, 2019, 50(6): 24-27,31.
    Citation: WEI Lianjiang, HU Qingwei, LIANG Wei, REN Fei. Research on Gas Abnormal Mode Diagnosis Based on K-line Theory[J]. Safety in Coal Mines, 2019, 50(6): 24-27,31.

    基于K线图理论的瓦斯异常模式诊断研究

    Research on Gas Abnormal Mode Diagnosis Based on K-line Theory

    • 摘要: 在归纳瓦斯监测数据异常模式的同时,从K线图角度对瓦斯异常模式进行研究,得出煤与瓦斯突出时呈大阳线形态,炮后瓦斯涌出呈二、三连阳等结论。据此确立瓦斯异常K线诊断准则,运用VB.NET程序设计语言编写了瓦斯异常K线诊断程序,通过对105条不同矿井瓦斯K线异常序列进行混合诊断,诊断准确率达到93.33%,普适性较强。

       

      Abstract: The gas anomaly pattern is studied from the angle of K-graph, at the same time, the abnormal mode of gas monitoring data is summed up. It is concluded that the coal and gas outburst is a big positive line, and the gas emission after the gun is two and three times positive. According to this, the diagnosis criterion of abnormal K-line of gas is established and the VB.NET programming language is used to compile the diagnosis program of abnormal K-line of gas. Through the mixed diagnosis of the abnormal K-line of gas in 105 different mines, the result shows that the accuracy rate is 93.33% and the universality is strong.

       

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