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| Establishment and application of microseismic monitoring system for water damage in Pingyu No.1 Mine |
| Yang Guangyue1, Gao Gang2 |
| 1. Henan Pingyu Coal Power Co., Ltd., Xuchang 461670, China; 2. Hebei Coal Research Institute Co.,Ltd.,Xingtai 054000,China |
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Abstract The mining of No.II1 coal seam in Pingyu No.1 Coal Mine was threatened by the water damage of floor limestone. The microseismic monitoring system of water damage was constructed by using the large-scale real-time continuous characteristics of microseismic monitoring. The correction shot was used to invert the source parameters to determine that the positioning error of the system met the requirements. The spatial distribution characteristics of microseismic events and the damage range of floor during mining were determined, and the correlation between mining speed and microseismic activity was studied. The results showed that the failure depth of the floor of the working face during the monitoring period was 14 ~ 16 m. Under the condition of stratified mining, the reasonable range of the daily advancing distance of No.II1-15010 Face was 1.5 ~ 1.8 m. During the monitoring period, there was no Cambrian limestone microseismic event, indicating that there was no deep water channel formation, which provided a basis for safe mining.
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| 1 ] 余国锋. 基于微震和神经网络的煤层底板突水预警技术研究[ D ]. 安徽:安徽理工大学,2022.
[ 2 ] 靳德武,段建华,李连崇,等. 基于微震的底板采动裂隙扩展及导水通道识别技术研究[ J ]. 工程地质学报,2021,29( 4 ):962 - 971.
[ 3 ] 程关文. 煤矿突水的微破裂前兆信息微震监测技术研究[ D ].大连:大连理工大学,2017.
[ 4 ] 查华胜,张海江,连会青,等. 潘二煤矿A组煤层底板灰岩水害微震监测[ J ]. 煤炭学报,2022,47( 8 ):3 001 - 3 014.
[ 5 ] 王 杰,李博凡,蒋齐平,等. 工作面采动影响下底板破坏深度微震规律[ J ]. 采矿与岩层控制工程学报,2022( 5 ):27 - 36.
[ 6 ] 王进尚,郭 俊,辛崇伟,等. 基于高精度微震监测技术的底板破坏深度预测研究[ J ]. 煤炭技术,2020,39( 4 ):67 - 70.
[ 7 ] 许延春,黄 磊. 基于微震监测的工作面底板突水全时空预警方法[ J ]. 煤炭科学技术,2023,51( 1 ):369 - 382.
[ 8 ] 陈炳瑞,吴 昊,池秀文,等. 基于STA/LTA岩石破裂微震信号实时识别算法及工程应用[ J ]. 岩土力学,2019,40( 9 ):3 689 - 3 696.
[ 9 ] 张党育,武 斌,贾 靖,等. 基于微震数据及模型的煤矿水害“双驱动”预警体系构建与应用[ J ]. 煤炭科学技术:1 - 18[2023 - 05 - 06].
[ 10 ] 周金艳,陈为民,赵立松. 煤层底板导水通道微震信号辨识特征[ J ]. 煤炭技术,2022,41( 12 ):128 - 134. |
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