WU Fusheng. Experimental study on composite gas indexes optimization for coal spontaneous combustion predictio[J]. Journal of Mine Automation, 2018, 44(7): 61-65. DOI: 10.13272/j.issn.1671-251x.17341
Citation: WU Fusheng. Experimental study on composite gas indexes optimization for coal spontaneous combustion predictio[J]. Journal of Mine Automation, 2018, 44(7): 61-65. DOI: 10.13272/j.issn.1671-251x.17341

Experimental study on composite gas indexes optimization for coal spontaneous combustion predictio

More Information
  • Changing rule of composite gas indexes under different dry air flow and oxygen concentration was analyzed through coal temperature-programmed experiment. The experimental results show that φ(O2)/(φ(CO)+φ(CO2)) should be selected as gas indexes for coal spontaneous combustion prediction in the case of uncertain dry air flow. φ(O2)/(φ(CO)+φ(CO2)) can be used as gas indexes for coal spontaneous combustion prediction when coal temperature is below 100 °C. φ(C2H4)/φ(CH4) and φ(CO)/φ(CO2) can be used as gas indexes for coal spontaneous combustion prediction when coal temperature exceeds 100 °C. φ(C2H4)/φ(CO) can also be used as gas indexes for coal spontaneous combustion when coal temperature exceeds 160 °C and oxygen volume fraction is approximately 5%.
  • Related Articles

    [1]YAN Guofeng, HUANG Xingli, YAN Zhenguo. Research on exothermic and kinetic characteristics of low-temperature oxidation of preoxidized coal[J]. Journal of Mine Automation, 2022, 48(7): 135-141. DOI: 10.13272/j.issn.1671-251x.2022030032
    [2]YAO Huawei, HE Xiaodong, WANG Zhe. Numerical study of pulverized coal ignition under different oxygen conditions based on solid-gas coupling[J]. Journal of Mine Automation, 2022, 48(3): 107-111, 117. DOI: 10.13272/j.issn.1671-251x.2021090068
    [3]FANG Xiyang, YAO Haifei. Experimental study on the displacement of oxygen in coal with different particle sizes by inert gas[J]. Journal of Mine Automation, 2021, 47(9): 101-107.. DOI: 10.13272/j.issn.1671-251x.17840
    [4]XI Bo, WANG Shi'ao, GUO Jianwei. Design of on-line detection system of mine emulsion concentratio[J]. Journal of Mine Automation, 2020, 46(9): 98-103. DOI: 10.13272/j.issn.1671-251x.2020040023
    [5]ZHANG Suorong, CHEN Jiange. Research of detection technology of metal dust concentratio[J]. Journal of Mine Automation, 2017, 43(3): 57-60. DOI: 10.13272/j.issn.1671-251x.2017.03.013
    [6]XU Xuezhan, MENG Xiangrui, ZOU Yunlong. Coal and gas outburst early-warning technology based on change of gas concentratio[J]. Journal of Mine Automation, 2016, 42(9): 17-21. DOI: 10.13272/j.issn.1671-251x.2016.09.005
    [7]GONG Zhongqiang, LI Jun, ZHANG Shulin, GUO Qinghua. Research of oxygen concentration and temperature detection system[J]. Journal of Mine Automation, 2015, 41(10): 20-23. DOI: 10.13272/j.issn.1671-251x.2015.10.006
    [8]ZHAO Si-hai, WANG Qi, LIU Zhi-qiang. Research Progress of Detection and Automatic Matching Technique for Emulsion Concentratio[J]. Journal of Mine Automation, 2012, 38(8): 30-35.
    [9]WANG Hong-jian, TANG Mao-feng, WANG Xue-ming, LIU Yan, SHENG Nan. Design of Mine-used High-precision Oxygen Sensor with Temperature Compensatio[J]. Journal of Mine Automation, 2012, 38(5): 63-65.
    [10]WU Yong, SONG Lei, QU Nai-rui. Research of Mine-used Blending Device of Emulsion Concentratio[J]. Journal of Mine Automation, 2012, 38(2): 84-87.
  • Cited by

    Periodical cited type(12)

    1. 马丙太,吴昊,周一文,嵇文磊,汪洋,赵德刚. 基于IPTA和SBAS-InSAR的闭坑矿井地表残余变形监测. 能源与环保. 2025(03): 123-128 .
    2. 桂智琛,徐良骥,刘潇鹏,曹宗友. 基于时序InSAR的关闭矿井地表残余沉降监测. 绿色矿山. 2024(01): 54-63 .
    3. 许时昂,吴海波,欧元超,席超强. 采煤沉陷松散层变形研究现状与分析. 科学技术与工程. 2024(17): 6999-7013 .
    4. 郑美楠,邓喀中,郭庆彪,赵若南,秦锡鹏. 淮南矿区关闭矿井地表次生沉陷InSAR监测与规律分析. 武汉大学学报(信息科学版). 2024(08): 1356-1366 .
    5. 刘增波,徐良骥,张坤,刘潇鹏,曹宗友,徐阳. 融合SBAS-InSAR与CS-SVM的矿区地表残余沉降预测模型. 金属矿山. 2024(08): 133-139 .
    6. 姜川,王磊杰,樊高强,李昊,李叶繁,苑雨,张曦. 基于SBAS-InSAR的郑州煤炭矿区地表沉降监测及演化规律分析. 中国煤炭. 2024(10): 158-165 .
    7. 魏勇,吉坤,阎鸣泽,李晅辉,刘迎,李宏,韩斌,戴靠山. 基于RSM-BBD方法的关闭/废弃矿井地热系统长期采热性能研究. 矿业研究与开发. 2024(12): 273-282 .
    8. 张连蓬,梁亮,陈炳乾,胡晋山,于洋,秦璐,余昊,杨家乐,杨宇. 基于SBAS-InSAR技术的关闭矿井地表多维形变时空监测与分析方法. 金属矿山. 2023(01): 83-94 .
    9. 高玉荣,隋刚,张新军,孔嘉嫄,张和生. 遥感方法在宁武煤田煤火识别中的应用. 煤炭科学技术. 2023(05): 133-139 .
    10. 褚召祥. 基于体积法的废弃煤矿水热型热储潜能评估. 工程地质学报. 2023(05): 1696-1710 .
    11. 秦锡鹏,邓喀中,郑美楠,王刘宇. 徐州西部关闭矿井地表次生沉陷监测与分析. 测绘科学. 2022(08): 247-254 .
    12. 梁思语,胡海峰. 基于SBAS-InSAR技术的采空区残余变形规律分析. 中国矿业. 2022(12): 70-78 .

    Other cited types(3)

Catalog

    Article Metrics

    Article views (110) PDF downloads (10) Cited by(15)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return