刘琼, 刘勇, 孙秉成, 张庆华, 王麒翔, 王沉. 乌东矿瓦斯涌出异常大数据技术研究与应用[J]. 煤矿安全, 2019, 50(10): 79-83.
    引用本文: 刘琼, 刘勇, 孙秉成, 张庆华, 王麒翔, 王沉. 乌东矿瓦斯涌出异常大数据技术研究与应用[J]. 煤矿安全, 2019, 50(10): 79-83.
    LIU Qiong, LIU Yong, SUN Bingcheng, ZHANG Qinghua, WANG Qixiang, WANG Chen. Big Data Research and Application for Abnormal Gas Emission in Wudong Mine[J]. Safety in Coal Mines, 2019, 50(10): 79-83.
    Citation: LIU Qiong, LIU Yong, SUN Bingcheng, ZHANG Qinghua, WANG Qixiang, WANG Chen. Big Data Research and Application for Abnormal Gas Emission in Wudong Mine[J]. Safety in Coal Mines, 2019, 50(10): 79-83.

    乌东矿瓦斯涌出异常大数据技术研究与应用

    Big Data Research and Application for Abnormal Gas Emission in Wudong Mine

    • 摘要: 利用理论分析和现场实测的方法研究了瓦斯涌出异常的影响因素及瓦斯涌出异常预警技术的实现流程。针对乌东矿瓦斯突出特征与规律,运用了大数据技术研究监控监测总体数据,研究了适合乌东矿的瓦斯突出预警指标体系中的趋势预警指标,并建立了乌东矿瓦斯涌出异常的数据模型,实现了工作面及掘进面瓦斯突出危险性的实时智能预警,在乌东矿的应用效果验证了该风险态势分析平台的有效性。

       

      Abstract: This paper studies the influencing factors of gas emission anomalies and the realization process of early warning technology for gas emission anomaly by theoretical analysis and field measurement. According to the characteristics and laws of gas outburst in Wudong Mine, big data technology is used to study gas monitoring data. The early warning index system for gas outburst suitable for Wudong Mine is studied, and the data model of gas emission anomaly in Wudong Mine is established. The real-time intelligent warning system for gas outburst hazard in working face and heading face is realized. The effectiveness of the platform is verified by the application results in Wudong Mine.

       

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