冻结立井爆破近区井壁振动信号基线漂移校正和消噪方法

付晓强 杨仁树 刘纪峰 张会芝 张仁巍

付晓强, 杨仁树, 刘纪峰, 张会芝, 张仁巍. 冻结立井爆破近区井壁振动信号基线漂移校正和消噪方法[J]. 爆炸与冲击, 2020, 40(9): 095203. doi: 10.11883/bzycj-2019-0367
引用本文: 付晓强, 杨仁树, 刘纪峰, 张会芝, 张仁巍. 冻结立井爆破近区井壁振动信号基线漂移校正和消噪方法[J]. 爆炸与冲击, 2020, 40(9): 095203. doi: 10.11883/bzycj-2019-0367
FU Xiaoqiang, YANG Renshu, LIU Jifeng, ZHANG Huizhi, ZHANG Renwei. Baseline drift correction and de-noising method of shaft lining vibration signal in near field of freezing vertical shaft blasting[J]. Explosion And Shock Waves, 2020, 40(9): 095203. doi: 10.11883/bzycj-2019-0367
Citation: FU Xiaoqiang, YANG Renshu, LIU Jifeng, ZHANG Huizhi, ZHANG Renwei. Baseline drift correction and de-noising method of shaft lining vibration signal in near field of freezing vertical shaft blasting[J]. Explosion And Shock Waves, 2020, 40(9): 095203. doi: 10.11883/bzycj-2019-0367

冻结立井爆破近区井壁振动信号基线漂移校正和消噪方法

doi: 10.11883/bzycj-2019-0367
基金项目: 三明学院引进高层次人才科研启动经费(18YG13)
详细信息
    作者简介:

    付晓强(1984- ),男,博士,讲师,fuxiaoqiang1984@163.com

  • 中图分类号: O389; TD235.1

Baseline drift correction and de-noising method of shaft lining vibration signal in near field of freezing vertical shaft blasting

  • 摘要: 冻结立井爆破过程中,近区监测信号中含有的基线漂零及噪声成分对其局部特征精细化提取影响显著。在对近区井壁振动信号有效采集基础上,通过互补总体经验模态分解(complementary ensemble empirical mode decomposition, CEEMD)方法、稀疏化基线估计消噪(baseline estimation and de-noising with sparsity, BEADS)方法和隐马尔可夫模型消噪(hidden Markov model de-noising, HMMD)方法等,解决了信号中基线漂移和随机噪声消除难题,并采用交叉小波变换对校正和消噪效果进行了相关性评价。实例分析结果表明:信号中缓变的基线成分遍历信号各个模态分量的整个过程,且主要集中于低频分量中,而噪声则集中在高频分量。组合分析方法对低频基线漂零和高频噪声的处理效果好,是一种高效且相对保幅的信号分析方法,可用于批量信号数据的预处理过程。
  • 图  1  基线校正及消噪流程

    Figure  1.  Baseline correction and noise reduction process

    图  2  传感器井壁预埋法

    Figure  2.  Pre-embedding method of vibration instrument

    图  3  炮眼布置(单位:mm)

    Figure  3.  Borehole layout (unit: mm)

    图  4  爆破近区井壁振动信号

    Figure  4.  Vibration signal of shaft lining near blasting area

    图  5  各IMF分量筛分迭代次数关系

    Figure  5.  The relationship of iterations number and shift number

    图  6  信号CEEMD分解各分量及残余项R

    Figure  6.  Component of CEEMD decomposition and residual signal

    图  7  模态分量处理结果

    Figure  7.  Results of baseline correction processing

    图  8  各分量基线成分

    Figure  8.  Baseline of each component

    图  9  罚函数值与迭代次数关系

    Figure  9.  Relation of cost function and the iteration number

    图  10  基线校正后信号

    Figure  10.  Baseline corrected signal

    图  11  CEEMD重构信号

    Figure  11.  Reconstructed signals of CEEMD

    图  12  消噪后的校正信号

    Figure  12.  Baseline corrected signal after de-noising

    图  13  信号功率谱密度(wf

    Figure  13.  Power spectral density (wf) of signal

    图  14  信号相关性凝聚谱

    Figure  14.  Correlation condensation spectra of signals

    表  1  模态分量与原信号相关度

    Table  1.   Correlation between components and original signals

    IMF相关性系数IMF相关性系数IMF相关性系数
    10.420250.502390.1083
    20.448460.1419100.3707
    30.375470.1333110.4540
    40.412480.1364120.2940
    下载: 导出CSV

    表  2  不同方法消噪性能指标

    Table  2.   Indexes of noise reduction performance

    去噪方法评价指标
    SNRRMSECCPE
    MD3.4420.5810.8161.758
    SVD20.9830.3790.8961.175
    WED21.3970.3740.9210.492
    HMMD43.3710.0560.9920.244
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-09-23
  • 修回日期:  2020-02-11
  • 网络出版日期:  2020-08-25
  • 刊出日期:  2020-09-01

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