崔聪, 李晓绅, 舒龙勇, 李宏艳, 马延崑, 周洋, 宋鑫. 瓦斯抽采达标智能决策平台的研发与应用[J]. 煤矿安全, 2022, 53(3): 120-124.
    引用本文: 崔聪, 李晓绅, 舒龙勇, 李宏艳, 马延崑, 周洋, 宋鑫. 瓦斯抽采达标智能决策平台的研发与应用[J]. 煤矿安全, 2022, 53(3): 120-124.
    CUI Cong, LI Xiaoshen, SHU Longyong, LI Hongyan, MA Yankun, ZHOU Yang, SONG Xin. Research and application of intelligent decision-making platform for gas excavation from standard[J]. Safety in Coal Mines, 2022, 53(3): 120-124.
    Citation: CUI Cong, LI Xiaoshen, SHU Longyong, LI Hongyan, MA Yankun, ZHOU Yang, SONG Xin. Research and application of intelligent decision-making platform for gas excavation from standard[J]. Safety in Coal Mines, 2022, 53(3): 120-124.

    瓦斯抽采达标智能决策平台的研发与应用

    Research and application of intelligent decision-making platform for gas excavation from standard

    • 摘要: 为了解决瓦斯抽采治理智能化程度低、瓦斯防治信息不完善、抽采模型忽视数据分析与态势预测等缺陷,构建了1套以物联网“1张图”为基础,以智能调优算法与“大数据”挖掘为核心的瓦斯抽采达标智能决策平台。开发了数据关联融合功能实现抽采达标实时评判;集成实时抽采数据与历史抽采数据,采用神经网络预测方法对瓦斯治理数据进行有指导的数据挖掘,实现瓦斯抽采模型智能预测;应用API方式进行GIS功能的定制,实现瓦斯防治井下应用场景可视化、井上瓦斯治理工作流程化。平台在冀中能源股份有限公司东庞矿得以应用,现场试验结果表明:该平台可有效减少煤矿技术人员的工作量及人工处理、人工预测可能带来的误差,实现瓦斯抽采防治工作透明,推动了瓦斯治理智能化发展。

       

      Abstract: In order to solve the defects of low intelligence in gas drainage and control, imperfect gas prevention and control information, and ignoring data analysis and situation prediction in gas drainage model, a set of intelligent decision-making platform for gas drainage standard is constructed based on the “one map” of the Internet of things and centered on intelligent optimization algorithm and “big data” mining. The data association and fusion function is developed to realize the real-time evaluation of pumping and production standards; integrating the real-time drainage data and historical drainage data, the neural network prediction method is used to guide the data mining of gas control data, so as to realize the intelligent prediction of gas drainage model; the API method is applied to customize the GIS function, so as to realize the visualization of underground application scene of gas prevention and control and the workflow of well gas control. The platform has been applied in Dongpang Mine of Jizhong Energy Co., Ltd. The field test results show that the platform can effectively reduce the workload of coal mine technicians and the possible errors caused by manual processing and manual prediction, realize the transparency of gas drainage and prevention, and promote the intelligent development of gas control.

       

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