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现代矿业 ›› 2024, Vol. 40 ›› Issue (06): 81-.

• • 上一篇    下一篇

煤矿掘进巷道微震监测b值优化及煤岩识别预警*

随着采掘工作面开采深度和强度的增加,煤矿井下微震事件与灾害风险在持续增高。
结合漳村煤矿掘进巷道微震监测数据,对掘进面前方区域微震事件b值优化分析和信息识别分类,提
出了基于最小二乘法的变分档根方算法,从“时、空、强”
3
个角度对断层区域进行了b值、震源的讨论
分析,提高了b值准确性。为微震事件的分类识别提供了方法和思路,更好地利用微震数据指导矿方
安全生产和防护。
  

  1. 1. 山西潞安环保能源开发股份有限公司漳村煤矿;
    2. 齐鲁工业大学(山东省科学院)激光研究所;
    3. 山东盛隆安全技术有限公司
  • 出版日期:2024-06-17 发布日期:2024-08-06

b-value Optimization and Information Identification and Early Warning of Tunning
in Coal Mine Roadway

With the increase of mining depth and intensity of mining face,the risk of microseismic
events and disasters in underground coal mines continues to increase. Combined with the microseismic moni⁃
toring data of the tunneling roadway in Zhangcun Coal Mine,the b-value optimization analysis and informa⁃
tion recognition classification of the microseismic events in the area in front of the tunneling face are carried
out. A variational root-square algorithm based on the least square method is proposed. A variational root
square algorithm based on the least square method is proposed. The b-value and source of the fault area are
analyzed from the three angles of ′time,space and strength′,and the accuracy of the b-value is optimized.
The research improves the reliability of microseismic monitoring and early warning and better guides mine
safety production.
  

  1. 1. Zhangcun Coal Mine,Shanxi Lu′an Environmental Protection Energy Development Co.,Ltd.;
    2. Laser Research Institute,Qilu University of Technology(Shandong Academy of Sciences);
    3. Shandong Shenglong Safety Technology Co.,Ltd.
  • Online:2024-06-17 Published:2024-08-06

摘要:

随着采掘工作面开采深度和强度的增加,煤矿井下微震事件与灾害风险在持续增高。
结合漳村煤矿掘进巷道微震监测数据,对掘进面前方区域微震事件b值优化分析和信息识别分类,提
出了基于最小二乘法的变分档根方算法,从“时、空、强”
3
个角度对断层区域进行了b值、震源的讨论
分析,提高了b值准确性。为微震事件的分类识别提供了方法和思路,更好地利用微震数据指导矿方
安全生产和防护。

关键词:

Abstract:

With the increase of mining depth and intensity of mining face,the risk of microseismic
events and disasters in underground coal mines continues to increase. Combined with the microseismic moni⁃
toring data of the tunneling roadway in Zhangcun Coal Mine,the b-value optimization analysis and informa⁃
tion recognition classification of the microseismic events in the area in front of the tunneling face are carried
out. A variational root-square algorithm based on the least square method is proposed. A variational root
square algorithm based on the least square method is proposed. The b-value and source of the fault area are
analyzed from the three angles of ′time,space and strength′,and the accuracy of the b-value is optimized.
The research improves the reliability of microseismic monitoring and early warning and better guides mine
safety production.

Key words:

roadway