Advance Search
Issue 5
May  2017
Turn off MathJax
Article Contents
Zhou Peng Zhang Bo, . Experimental study on water sensitivity of shear strength of extremely soft coal seam[J]. COAL SCIENCE AND TECHNOLOGY, 2017, (5).
Citation: Zhou Peng Zhang Bo, . Experimental study on water sensitivity of shear strength of extremely soft coal seam[J]. COAL SCIENCE AND TECHNOLOGY, 2017, (5).

Experimental study on water sensitivity of shear strength of extremely soft coal seam

More Information
  • Available Online: April 02, 2023
  • Published Date: May 24, 2017
  • In order to analyze the effects of preventing rib spalling by using water injection in extremely soft coal seam, the change of shear strength after water inj ection was carried out on extremely soft coal seam.Based on the theory of unsaturated soil theory and the direct shear tests, by using extremely soft coal samples whic h had been re-modelled, a series of direct shear tests with non consolidation and non drainage were performed under the conditions of different moisture contents and different normal stresses. The analysis method of shear strength was proposed in this paper, and the moisture content was used as the key index, the cohesion and int ernal friction angle were selected as the main indexes. The influences of moisture content on extremely soft coal seam were studied comprehensively combined with te sts and theoretical analysis.Results showed that in the condition of low normal stress, the shear strength of the sample tended to soften, and the sample was prone to h ardening in high stress state. Besides, the cohesion increased with the increasing of the moisture content, after that when the moisture content of the sample exceeded the optimum moisture content ( approximately 17.64%),the cohesion began to decline and the moisture content possesses lttle effect on the internal friction angle. It i s proved that the engineering control technology of preventing rib spalling by using water injection in extremely soft coal seam is effective.
  • Cited by

    Periodical cited type(15)

    1. 焦建英,吕春颖,邵暖,张贺玉,张翔,武智瑛. 基于C#+PLC煤矿边缘监测AI控制研究. 煤炭技术. 2025(04): 235-238 .
    2. 王昕彤. 基于大数据和人工智能的矿山安全预警与监控. 信息与电脑(理论版). 2024(01): 202-204 .
    3. 郝守礼,乔燕军,范科,赵文韬,丁洒. 光伏发电区红外热成像火灾预警系统研究. 信息与电脑(理论版). 2024(05): 59-61 .
    4. 田佳伟,唐子山. 基于边缘计算和ST-YOLO的矿井智能监控技术研究. 煤炭工程. 2024(07): 165-173 .
    5. 都书刚,戴万波,马旭伟,康舆哲. 智能矿山IoT边缘数据网关技术研究. 矿冶. 2024(04): 631-636 .
    6. 张婧,周浩,屈世甲,赵乾坤. 工作面煤壁甲烷涌出在受限空间的扩散规律研究. 煤炭技术. 2024(10): 135-141 .
    7. 张婧,张桓瑞,赵乾坤,屈世甲. 综采工作面区域甲烷分布特征及关键监测位置研究. 中国矿业. 2024(10): 209-216 .
    8. 崔林林,权晓光,徐昊,仝依良,王晓彬. 基于Azure边云结合在煤矿安全方向应用研究. 传感器与微系统. 2024(12): 37-40 .
    9. 王健,屈世甲,于振,张羽. 煤矿地下水库安全监测及预警关键技术研究. 中国煤炭. 2024(12): 71-82 .
    10. 安军. 基于无线通信技术的电气火灾智能监控系统. 自动化与仪表. 2023(01): 120-124 .
    11. 程德强,钱建生,郭星歌,寇旗旗,徐飞翔,顾军,高亚超,赵金升. 煤矿安全生产视频AI识别关键技术研究综述. 煤炭科学技术. 2023(02): 349-365 . 本站查看
    12. 杨波. 基于大数据分析的煤矿通风自动控制系统. 能源与环保. 2023(08): 39-44 .
    13. 李伟,叶鸥,刘辉,黄天尘. 基于数字孪生技术的大型煤矿远程智能监控研究. 计算机测量与控制. 2023(11): 204-211 .
    14. 刘辉,张晓利,黄天尘,赵堃. 基于改进RBF数据融合算法的煤矿井下安全监控研究. 计算机测量与控制. 2023(11): 173-180 .
    15. 蔡勇. 煤矿安全监测监控系统在应用中存在的问题及解决措施分析. 内蒙古煤炭经济. 2022(24): 94-96 .

    Other cited types(3)

Catalog

    Article views (403) PDF downloads (273) Cited by(18)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return