基于EEMD_Hankel_SVD的矿山微震信号降噪方法
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摘要
针对矿山微震信号降噪,提出了一种基于EEMD_Hankel_SVD(集合经验模态分解_Hankel矩阵_奇异值分解)的微震信号降噪方法。首先采用EEMD获得多层模态分量,计算各模态分量与原始信号的相关系数,剔除第一个相关系数差值局部最大值前的模态分量。对剩余各模态分量分别构建Hankel矩阵,再计算各Hankel矩阵的奇异值矩阵。根据奇异值曲线划分信号空间和噪声空间,实现剩余各模态分量的降噪,进而对降噪后的模态分量相加得到降噪信号。仿真试验表明该方法能有效保留信号的局部特征,提高了信噪比;矿山微震信号应用表明该方法有效地提高了STA/LTA,PAI-K和AIC法P波初至拾取效果;仿真试验和矿山微震信号P波拾取均表明该方法降噪效果优于小波重构、EMD重构和Hankel_SVD降噪,且该方法与AIC法结合拾取效果最佳。
To denoise microseismic noises,an EEMD_Hankel_SVD(ensemble empirical mode decomposition_Hankel matrix_signular value decomposition) combined method is proposed. Firstly,the EEMD is used to obtain mode functions,then the correlation coefficient between each mode function and original signal is calculated,and the mode functions before the first local maximum correlation coefficient difference are deleted. The rest mode functions are used to construct Hankel matrixes,and the SVD is applied to decompose the Hankel matrixes.The microseismic signal and noises are divided by the curve of singular values and this is used to denoise mode functions,then the denoised mode functions are combined to obtain denoised microseismic signal.The simulated tests show that the proposed method can retain local features well and increase signal to noise ratio(SNR).The application to mine microseismic signals shows that the proposed method can effectively improve the P-phase picking results of the STA/LTA picker,PAI-K(phase arrival identification-kurtosis) picker and AIC(Akaike information criterion) picker. In addition,both the simulated tests and mine microseismic signal picking results show that the denoising performance of this method is better than that of wavelet reconstruction,empirical mode decomposition(EMD) reconstruction,and Hankel_SVD denoising.Fur-thermore,the combination with the AIC picker obtains a best picking result.
To denoise microseismic noises,an EEMD_Hankel_SVD(ensemble empirical mode decomposition_Hankel matrix_signular value decomposition) combined method is proposed. Firstly,the EEMD is used to obtain mode functions,then the correlation coefficient between each mode function and original signal is calculated,and the mode functions before the first local maximum correlation coefficient difference are deleted. The rest mode functions are used to construct Hankel matrixes,and the SVD is applied to decompose the Hankel matrixes.The microseismic signal and noises are divided by the curve of singular values and this is used to denoise mode functions,then the denoised mode functions are combined to obtain denoised microseismic signal.The simulated tests show that the proposed method can retain local features well and increase signal to noise ratio(SNR).The application to mine microseismic signals shows that the proposed method can effectively improve the P-phase picking results of the STA/LTA picker,PAI-K(phase arrival identification-kurtosis) picker and AIC(Akaike information criterion) picker. In addition,both the simulated tests and mine microseismic signal picking results show that the denoising performance of this method is better than that of wavelet reconstruction,empirical mode decomposition(EMD) reconstruction,and Hankel_SVD denoising.Fur-thermore,the combination with the AIC picker obtains a best picking result.
引文
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[9]李稳,刘伊克,刘保金.基于稀疏分布特征的井下微地震信号识别与提取方法[J].地球物理学报,2016,59(10):3869-3882.LI Wen,LIU Yike,LIU Baojin.Downhole microseismic signal recognition and extraction based on sparse distribution features[J].Chinese Journal of Geophysics,2016,59(10):3869-3882.
[10]BEENAMOL M,PRABAVATHY S,MOHANALIN J.Wavelet based seismic signal de-noising using Shannon and Tsallis entropy[J].Computers&Mathematics with Applications,2012,64(11):3580-3593.
[11]ZHANG H.Automatic P-wave arrival detection and picking with multiscale wavelet analysis for single-component recordings[J].Bulletin of the Seismological Society of America,2003,93(5):1904-1912.
[12]OMITAOMU O A,PROTOPOPESCU V A,GANGULY A R.Empirical mode decomposition technique with conditional mutual information for denoising operational sensor data[J].IEEE Sensors Journal,2011,11(10):2565-2575.
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[14]贾瑞生,谭云亮,孙红梅,等.低信噪比微震P波震相初至自动拾取方法[J].煤炭学报,2015,40(8):1845-1852.JIA Ruisheng,TAN Yunliang,SUN Hongmei,et al.Method of automatic detection on micro-seismic P-arrival time under low signal-to-noise ratio[J].Journal of China Coal Society,2015,40(8):1845-1852.
[15]贾瑞生,赵同彬,孙红梅,等.基于经验模态分解及独立成分分析的微震信号降噪方法[J].地球物理学报,2015,58(3):1013-1023.JIA Ruisheng,ZHAO Tongbin,SUN Hongmei,et al.Micro-seismic signal denoising method based on empirical mode decomposition and independent component analysis[J].Chinese Journal of Geophysics,2015,58(3):1013-1023.
[16]梁喆,彭苏萍,郑晶.基于EMD和互信息熵的微震信号自适应去噪[J].计算机工程与应用,2014,50(4):7-11.LIANG Zhe,PENG Suping,ZHENG Jing.Self-adaptive denoising for microseismic signal based on EMD and mutual information entropy[J].Computer Engineering and Applications,2014,50(4):7-11.
[17]WU Z H,HUANG N E.Ensemble empirical mode decomposition:A noise-assisted data analysis method[J].Advances in Adaptive Data Analysis,2009,1(1):1-41.
[18]HAN J,MIRKO V D B.Microseismic and seismic denoising via ensemble empirical mode decomposition and adaptive thresholding[J].Geophysics,2015,80(6):KS69–KS80.
[19]TORRES M E,COLOMINAS M A,SCHLOTTHAUER G,et al.A complete ensemble empirical mode decomposition with adaptive noise[A].IEEE International Conference on Acoustics,Speech and Signal Processing[C].IEEE,2011:4144-4147.
[20]ZHAO X,YE B.Similarity of signal processing effect between Hankel matrix-based SVD and wavelet transform and its mechanism analysis[J].Mechanical Systems&Signal Processing,2009,23(4):1062-1075.
[21]SANLITURK K Y,CAKAR O.Noise elimination from measured frequency response functions[J].Mechanical Systems&Signal Processing,2005,19(3):615-631.
[22]田优平,赵爱华.基于小波包和峰度赤池信息量准则的P波震相自动识别方法[J].地震学报,2016,38(1):71-85.TIAN Youping,ZHAO Aihua.Automatic identification of P-phase based on wavelet packet and Kurtosis-AIC method[J].Acta Seismologica Sinica,2016,38(1):71-85.
[23]LI X B,SHANG X Y,MORALES-ESTEBAN A,et al.Identifying P phase arrival of weak events:The Akaike information criterion picking application based on the empirical mode decomposition[J].Computers&Geosciences,2017,100:57-66.
[2]李伟.基于LMD和模式识别的矿山微震信号特征提取及分类方法[J].煤炭学报,2017,42(5):1156-1164.LI Wei.Feature extraction and classification method of mine microseismic signals based on LMD and pattern recognition[J].Journal of China Coal Society,2017,42(5):1156-1164.
[3]PYTEL W,S'WITO N'J,W O'JCIK A.The effect of mining face’s direction on the observed seismic activity[J].International Journal of Coal Science&Technology,2016,3(3):322-329.
[4]徐宏斌,李庶林,陈际经.基于小波变换的大尺度岩体结构微震监测信号去噪方法研究[J].地震学报,2012,34(1):85-96.XU Hongbin,LI Shulin,CHEN Jijing.A study on method of signal denoising based on wavelet transform for micro-seismicity monitoring in large-scale rockmass structures[J].Acta Seismologica Sinica,2012,34(1):85-96.
[5]李学龙,李忠辉,王恩元,等.矿山微震信号干扰特征及去噪方法研究[J].中国矿业大学学报,2015,44(5):788-792.LI Xuelong,LI Zhonghui,WANG Enyuan,et al.Study of mine microseismic signals interference characteristic and its de-noising method[J].Journal of China University of Mining&Technology,2015,44(5):788-792.
[6]金晶晶,王旭,吴雪,等.基于改进阈值函数的体震信号平移不变去噪[J].东北大学学报(自然科学版),2009,30(3):333-336.JIN Jingjing,WANG Xu,WU Xue,et al.Translation-invariant de-noising of body fluttering signal based on improved threshold function[J].Journal of Northeastern University(Natural Science),2009,30(3):333-336.
[7]曹思远,陈香朋.第二代小波变换及其在地震信号去噪中的应用[J].应用地球物理(英文版),2005,43(2):547-550.CAO Siyuan,CHEN Xiangpeng.The second-generation wavelet transform and its application in denoising of seismic data[J].Applied Geophysics(English Version),2005,43(2):547-550.
[8]MOUSAVI S M,LANGSTON C A,HORTON S P.Automatic microseismic denoising and onset detection using the synchrosqueezed continuous wavelet transform[J].Geophysics,2016,81(4):V341-V355.
[9]李稳,刘伊克,刘保金.基于稀疏分布特征的井下微地震信号识别与提取方法[J].地球物理学报,2016,59(10):3869-3882.LI Wen,LIU Yike,LIU Baojin.Downhole microseismic signal recognition and extraction based on sparse distribution features[J].Chinese Journal of Geophysics,2016,59(10):3869-3882.
[10]BEENAMOL M,PRABAVATHY S,MOHANALIN J.Wavelet based seismic signal de-noising using Shannon and Tsallis entropy[J].Computers&Mathematics with Applications,2012,64(11):3580-3593.
[11]ZHANG H.Automatic P-wave arrival detection and picking with multiscale wavelet analysis for single-component recordings[J].Bulletin of the Seismological Society of America,2003,93(5):1904-1912.
[12]OMITAOMU O A,PROTOPOPESCU V A,GANGULY A R.Empirical mode decomposition technique with conditional mutual information for denoising operational sensor data[J].IEEE Sensors Journal,2011,11(10):2565-2575.
[13]HUANG N E,SHEN Z,LONG S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of the Royal Society of London,Series A,1998,454:903-995.
[14]贾瑞生,谭云亮,孙红梅,等.低信噪比微震P波震相初至自动拾取方法[J].煤炭学报,2015,40(8):1845-1852.JIA Ruisheng,TAN Yunliang,SUN Hongmei,et al.Method of automatic detection on micro-seismic P-arrival time under low signal-to-noise ratio[J].Journal of China Coal Society,2015,40(8):1845-1852.
[15]贾瑞生,赵同彬,孙红梅,等.基于经验模态分解及独立成分分析的微震信号降噪方法[J].地球物理学报,2015,58(3):1013-1023.JIA Ruisheng,ZHAO Tongbin,SUN Hongmei,et al.Micro-seismic signal denoising method based on empirical mode decomposition and independent component analysis[J].Chinese Journal of Geophysics,2015,58(3):1013-1023.
[16]梁喆,彭苏萍,郑晶.基于EMD和互信息熵的微震信号自适应去噪[J].计算机工程与应用,2014,50(4):7-11.LIANG Zhe,PENG Suping,ZHENG Jing.Self-adaptive denoising for microseismic signal based on EMD and mutual information entropy[J].Computer Engineering and Applications,2014,50(4):7-11.
[17]WU Z H,HUANG N E.Ensemble empirical mode decomposition:A noise-assisted data analysis method[J].Advances in Adaptive Data Analysis,2009,1(1):1-41.
[18]HAN J,MIRKO V D B.Microseismic and seismic denoising via ensemble empirical mode decomposition and adaptive thresholding[J].Geophysics,2015,80(6):KS69–KS80.
[19]TORRES M E,COLOMINAS M A,SCHLOTTHAUER G,et al.A complete ensemble empirical mode decomposition with adaptive noise[A].IEEE International Conference on Acoustics,Speech and Signal Processing[C].IEEE,2011:4144-4147.
[20]ZHAO X,YE B.Similarity of signal processing effect between Hankel matrix-based SVD and wavelet transform and its mechanism analysis[J].Mechanical Systems&Signal Processing,2009,23(4):1062-1075.
[21]SANLITURK K Y,CAKAR O.Noise elimination from measured frequency response functions[J].Mechanical Systems&Signal Processing,2005,19(3):615-631.
[22]田优平,赵爱华.基于小波包和峰度赤池信息量准则的P波震相自动识别方法[J].地震学报,2016,38(1):71-85.TIAN Youping,ZHAO Aihua.Automatic identification of P-phase based on wavelet packet and Kurtosis-AIC method[J].Acta Seismologica Sinica,2016,38(1):71-85.
[23]LI X B,SHANG X Y,MORALES-ESTEBAN A,et al.Identifying P phase arrival of weak events:The Akaike information criterion picking application based on the empirical mode decomposition[J].Computers&Geosciences,2017,100:57-66.