• Chinese Core Periodicals
  • Chinese Core Journals of Science and Technology
  • RCCSE Chinese Authoritative Academic Journals
LU Xinming, ZHANG Tianyu, WANG Yong, TU Hui, WANG Hongjuan. Discrete and Modal Early Warning of Coal and Gas Outburst Based on Time Series of Gas Emission[J]. Safety in Coal Mines, 2020, 51(11): 175-179.
Citation: LU Xinming, ZHANG Tianyu, WANG Yong, TU Hui, WANG Hongjuan. Discrete and Modal Early Warning of Coal and Gas Outburst Based on Time Series of Gas Emission[J]. Safety in Coal Mines, 2020, 51(11): 175-179.

Discrete and Modal Early Warning of Coal and Gas Outburst Based on Time Series of Gas Emission

More Information
  • Published Date: November 19, 2020
  • In order to realize the dynamic and real-time early warning of coal and gas outburst danger in working face, a discrete modal early warning method based on time series of gas emission is proposed. The methane monitoring data of the coal mine in the real time was used to calculate the gas emission, then the discrete time series of gas emission is generated and the interval is divided. The critical values of early warning indicators for coal and gas outburst were determined according to the gas geological conditions of the mine, the occurrence status of coal seams in the mining area, the mechanism of gas disasters, the historical records of gas emission anomalies, and the precursor information records of gas outbursts in similar working faces. According to the comparison between the modal parameters of the time series and the critical values of the early-warning indicators, the early-warning results of coal and gas outburst danger are released.
  • [1]
    于不凡,王佑安.煤矿瓦斯灾害防治及利用技术手册[M].北京:煤炭工业出版社,2005.
    [2]
    宁小亮.煤与瓦斯突出预警技术研究现状及发展趋势[J].工矿自动化,2019,45(8):25-37.
    [3]
    宁德义.我国煤矿瓦斯防治技术的研究进展及发展方向[J].煤矿安全,2016,47(2):161-165.
    [4]
    董丁稳,屈世甲,王红刚.基于多测点关联分析的工作面瓦斯浓度实时预警[J].中国安全科学学报,2015, 25(1):111-115.
    [5]
    朱世松,汪云甲,魏连江.基于时间序列相似性度量的瓦斯报警信号辨识[J].中国矿业大学学报,2012,41(3):474-480.
    [6]
    魏连江,胡青伟,梁伟,等.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.
    [7]
    李胜,罗明坤,范超军,等.采煤工作面煤与瓦斯突出危险性智能判识技术[J].中国安全科学学报,2016, 26(10):76-81.
    [8]
    温廷新,孙雪,孔祥博,等.基于PSOBP-AdaBoost模型的瓦斯涌出量分源预测研究[J].中国安全科学学报,2016,26(5):94-98.
    [9]
    时天,马宪民.基于径向基神经网络的煤矿工作面瓦斯预测研究[J].仪器仪表学报,2008,29(4):618.
    [10]
    郭德勇,胡杰,王彦凯.煤与瓦斯突出层次-可拓预警技术及应用[J].中国安全科学学报,2017,27(1):88-92.
    [11]
    杜振宇,薛俊华,任波,等.基于层次-可拓的煤与瓦斯突出预警研究[J].煤矿安全,2018,49(12):169.
    [12]
    王巍,刘德胜.基于支持向量机理论的煤矿瓦斯涌出量预测研究[J].煤矿机械,2011,32(2):78-80.
    [13]
    崔邯龙,李海涛,孟文清.综掘工作面瓦斯涌出量的支持向量机预测模型[J].煤炭工程,2009(2):75.
    [14]
    孟絮屹.灰色理论在煤与瓦斯突出预测中的应用研究[J].现代矿业,2015,31(5):119-120.
    [15]
    孙斌.瓦斯涌出量灰色预测[J].中国煤炭,2007,33(8):72-74.
    [16]
    吕品,马云歌,周心权.上隅角瓦斯浓度动态预测模型的研究及应用[J].煤炭学报,2006,31(4):461.
    [17]
    李伟山,王琳,卫晨.LSTM在煤矿瓦斯预测预警系统中的应用与设计[J].西安科技大学学报,2018,38(6):1027-1035.
    [18]
    卢新明,尹红.一种基于实时监测数据的动力灾害模态预警方法:CN108506041A[P].2018-09-07.
  • Related Articles

    [1]DENG Jun, ZHANG Qi, CNEN Weile, BAI Zujin. Coal spontaneous combustion disaster monitoring and early warning technologies and development trend for coal mines[J]. Safety in Coal Mines, 2024, 55(3): 99-110. DOI: 10.13347/j.cnki.mkaq.20231578
    [2]SHI Shiliang, ZENG Mingsheng, LI He, LU Yi. Coal spontaneous combustion and gas symbiotic disasters evolution and early warning[J]. Safety in Coal Mines, 2022, 53(9): 9-16.
    [3]ZHANG Guanghui, DENG Zhigang, JIANG Junjun, AN Yujia. Application of KJ768 Micro-seismic Monitoring System in Early Warning of Strong Mine Pressure Disaster in High Gassy Mines[J]. Safety in Coal Mines, 2020, 51(9): 144-147.
    [4]QU Shijia, WU Fusheng. Study on Environmental Safety Monitoring and Early Warning Method of Intelligent Working Face for Coal Mines[J]. Safety in Coal Mines, 2020, 51(8): 132-135.
    [5]GAO Jiancheng, NING Xiaoliang, QIN Muguang. Application of Coal Seam Outburst Prevention and Early Warning Technology in Deep Dynamic Disasters of Pingmei No.13 Coal Mine[J]. Safety in Coal Mines, 2020, 51(5): 150-153.
    [6]QIN Bingwen, XIE Fuxing. Disaster Mechanism and Early Warning System of Stope Roof[J]. Safety in Coal Mines, 2018, 49(5): 124-127.
    [7]XU Lei, LI Xijian. Mine Disaster Warning Model Based on Big Data[J]. Safety in Coal Mines, 2018, 49(3): 98-101.
    [8]XU Junjian. Prediction and Warning Technology of Working Face Roof Disaster[J]. Safety in Coal Mines, 2015, 46(11): 88-90,96.
    [9]LI Ming-jian, ZHANG Qing-Hua, HAN Wen-Ji. Design on Mine Map Editor Framework of Gas Disaster Early Warning System[J]. Safety in Coal Mines, 2013, 44(8): 88-90.
    [10]WANG Da-wei. Application of Ventsim Software in Disaster Warning of Deep Mining[J]. Safety in Coal Mines, 2012, 43(10): 107-108.
  • Cited by

    Periodical cited type(8)

    1. 陈祖国,张宁博,高园园,王晓鹏,黄霓,李洋. 基于多传感器信息融合的煤与瓦斯突出预警模型研究. 中国煤炭. 2024(06): 67-73 .
    2. 张志刚,张庆华,刘军. 我国煤与瓦斯突出及复合动力灾害预警系统研究进展及展望. 煤炭学报. 2024(S2): 911-923 .
    3. 兰海平,张志刚,徐再刚,田祥贵,张少超. 基于LSTM的瓦斯浓度预测与防突预警系统设计. 矿业安全与环保. 2023(02): 64-70 .
    4. 李菁. 基于区块链技术的煤炭运输安全预警研究. 能源与环保. 2022(02): 127-131+137 .
    5. 宋容. 基于多层关联规则算法的煤矿突出预警模型. 能源与环保. 2022(06): 300-305 .
    6. 朱墨然,王麒翔,张庆华. 多源数据驱动的防突预警指标自适应技术研究. 煤炭科学技术. 2022(08): 75-81 .
    7. 张智臣. 煤矿瓦斯灾害防治用新型地面钻机设计研究. 内蒙古煤炭经济. 2022(15): 11-13 .
    8. 林源. 基于云物元模型的煤与瓦斯突出危险性评估模型研究. 现代矿业. 2021(03): 234-235+241 .

    Other cited types(3)

Catalog

    Article views (31) PDF downloads (2) Cited by(11)

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return