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基于改进支持向量机的微震初至波到时自动拾取方法

李铁牛 胡宾鑫 李化坤 耿文成 郝鹏程 纪旭波 孙增荣 朱峰 张华 阳铖权

李铁牛,胡宾鑫,李化坤,等. 基于改进支持向量机的微震初至波到时自动拾取方法[J]. 工矿自动化,2023,49(3):63-69.  doi: 10.13272/j.issn.1671-251x.2022050081
引用本文: 李铁牛,胡宾鑫,李化坤,等. 基于改进支持向量机的微震初至波到时自动拾取方法[J]. 工矿自动化,2023,49(3):63-69.  doi: 10.13272/j.issn.1671-251x.2022050081
LI Tieniu, HU Binxin, LI Huakun, et al. Automatic picking method of microseismic first arrival time based on improved support vector machine[J]. Journal of Mine Automation,2023,49(3):63-69.  doi: 10.13272/j.issn.1671-251x.2022050081
Citation: LI Tieniu, HU Binxin, LI Huakun, et al. Automatic picking method of microseismic first arrival time based on improved support vector machine[J]. Journal of Mine Automation,2023,49(3):63-69.  doi: 10.13272/j.issn.1671-251x.2022050081

基于改进支持向量机的微震初至波到时自动拾取方法

doi: 10.13272/j.issn.1671-251x.2022050081
基金项目: 济宁市重点研发计划项目(2021AQGX001);山东省自然科学基金博士基金项目(ZR2019BEE019);山东省自然科学基金重点项目(ZR2020KC012);济南市“高校20条”资助项目(2020GXRC032);济南市“新高校20条”资助项目(2021GXRC037)。
详细信息
    作者简介:

    李铁牛(1997—),男,山东济南人,硕士研究生,研究方向为信息处理技术,E-mail:Tieniul@163.com

    通讯作者:

    胡宾鑫(1979—),男,浙江景宁人,副研究员,博士,研究方向为传感器技术与智能系统,E-mail:bxhu@qlu.edu.cn

  • 中图分类号: TD324

Automatic picking method of microseismic first arrival time based on improved support vector machine

  • 摘要: 微震初至波到时拾取是实现微震震源高精度定位的重要前提。传统的人工拾取方法效率低,而自动拾取方法在低信噪比条件下难以准确拾取初至波到时。针对上述问题,提出了一种基于改进支持向量机(SVM)的微震初至波到时自动拾取方法。首先,对原始微震数据进行归一化处理、线性校正和适当裁剪,将微震数据的振幅、能量和相邻时刻的能量比作为特征对数据标记不同类别;然后采用粒子群优化(PSO)算法和网格搜索法优化SVM的惩罚参数和核函数参数,即先利用PSO算法对参数进行大范围的快速定位,得到初步最优解,再以该解为初始位置重新构建参数搜索区间,设置小步长的网格搜索法对参数进行精细搜寻,得到最优参数,并将该最优参数代入SVM模型进行训练,得到改进SVM模型;最后根据改进的SVM模型对微震数据进行分类识别,定义微震波第1个采样点对应的时刻为初至波到时。采用某矿井下微震监测数据进行实验,结果表明:该方法对微震初至波到时的拾取准确率达96.5%,平均拾取误差为3.8 ms,在低信噪比情况下仍可对微震初至波到时进行准确拾取,拾取精度高于自动拾取方法中常用的长短时窗能量比(STA/LTA)法。

     

  • 图  1  最优分类超平面

    Figure  1.  Optimal classification hyperplane

    图  2  SVM结构

    Figure  2.  Support vector machine structure

    图  3  基于改进SVM的微震初至波到时自动拾取流程

    Figure  3.  Automatic picking process of microseismic first-arrival time based on improved support vector machine

    图  4  数据预处理流程

    Figure  4.  Data preprocessing process

    图  5  网格搜索法参数寻优结果

    Figure  5.  Parameter optimization results of grid search algorithm

    图  6  微震信号加噪后初至波到时拾取结果

    Figure  6.  First-arrival time picking results after microseismic signal plus noise

    图  7  8通道微震初至波到时拾取结果

    Figure  7.  8-channel microseismic first-arrival time picking results

    表  1  微震初至波到时统计结果

    Table  1.   Statistical results of microseismic first-arrival time

    微震
    检波器
    序号
    微震
    信号
    数量/组
    人工
    拾取
    数量/组
    自动拾取
    数量/组
    拾取
    准确率/%
    拾取
    误差/ms
    STA/
    LTA法
    本文
    方法
    STA/
    LTA法
    本文
    方法
    STA/
    LTA法
    本文
    方法
    136035732335190.598.36.53.5
    236035531534388.796.67.34.2
    336035631834689.397.25.92.9
    436035230733587.295.27.44.5
    536035431633989.295.86.73.4
    636035231133488.394.97.55.1
    736035733134892.797.56.93.7
    836035531234187.996.17.14.3
    936035832935391.998.66.32.7
    1036035431633689.394.96.93.9
    1136035330933587.594.97.74.2
    1236035632234890.497.86.63.6
    平均值360354.9317.4342.4 89.496.5 6.93.8
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-05-30
  • 修回日期:  2023-03-09
  • 网络出版日期:  2022-10-14

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