田宏海, 王东华, 刘晓明, 马延平, 王云飞, 黄艳伟. 桦树沟铜矿智能微震监测系统及其应用研究[J]. 中国矿业, 2021, 30(9): 80-87,96. DOI: 10.12075/j.issn.1004-4051.2021.09.024
    引用本文: 田宏海, 王东华, 刘晓明, 马延平, 王云飞, 黄艳伟. 桦树沟铜矿智能微震监测系统及其应用研究[J]. 中国矿业, 2021, 30(9): 80-87,96. DOI: 10.12075/j.issn.1004-4051.2021.09.024
    TIAN Honghai, WANG Donghua, LIU Xiaoming, MA Yanping, WANG Yunfei, HUANG Yanwei. Study on intelligent microseismic monitoring system and its application in Huashugou copper mine[J]. CHINA MINING MAGAZINE, 2021, 30(9): 80-87,96. DOI: 10.12075/j.issn.1004-4051.2021.09.024
    Citation: TIAN Honghai, WANG Donghua, LIU Xiaoming, MA Yanping, WANG Yunfei, HUANG Yanwei. Study on intelligent microseismic monitoring system and its application in Huashugou copper mine[J]. CHINA MINING MAGAZINE, 2021, 30(9): 80-87,96. DOI: 10.12075/j.issn.1004-4051.2021.09.024

    桦树沟铜矿智能微震监测系统及其应用研究

    Study on intelligent microseismic monitoring system and its application in Huashugou copper mine

    • 摘要: 镜铁山桦树沟铜矿发育有三组断层,矿山岩体结构完整,岩石强度高,受三组断裂构造的影响,开采过程中易发生矿山工程地质问题,巷道内片帮冒顶灾害频发,矿山生产安全受到极大威胁。因此,在镜铁山桦树沟矿区部署微震监测系统,并在应用过程中开展基于深度学习技术的微震数据智能化数据处理与分析研究,具有重要的现实意义。根据矿山生产实况,利用K-means聚类分析算法将矿区分为5个监测分区,同时形成以微震事件日频数、微震事件累积数目、βn分布及累积能量释放变化CUFIT模型等预警参数和方法为基础的一套有效可靠的灾害预警方法。研究结果成功地对矿区内监测分区四的地压灾害事件进行了预警。

       

      Abstract: There are three groups of faults developed in Huashugou copper mine of Jingtieshan.The rock mass structure of the mine is complete and the rock strength is high.Affected by the three groups of faults, the mine engineering geological problems are easy to occur in the mining process, and the roof fall disasters occur frequently in the roadway.The mine production safety is greatly threatened.Therefore, it is of great practical significance to deploy the microseismic monitoring system in Huashugou mining area of Jingtieshan and carry out the research on the intelligent data processing and analysis of microseismic data based on deep learning technology.According to the actual production situation of the mine, the mining area is divided into five monitoring zones by K-means clustering analysis algorithm.At the same time, a set of effective and reliable disaster early warning method based on the daily frequency of microseismic events, the cumulative number of microseismic events, distribution of βn and CUFIT model and other early warning parameters and methods of cumulative energy release change is formed.The study results have successfully given early warning to the ground pressure disaster events in monitoring fourth division of the mining area.

       

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