基于频域稀疏分解的大地电磁工频干扰压制（英文）
|
摘要
工频干扰是指由电网产生的基频及其奇次谐波干扰,它是大地电磁信号采集过程中最为普遍的干扰之一。尽管大部分采集设备都设计有抑制工频干扰的陷波电路,但由于电网中电流的实际频率会随着负载的变化有所波动,而陷波器的中心频率是固定的,因此在实际采集时,大地电磁信号依然受到工频噪声的严重影响。实践经验表明,当受工频干扰影响时,远参考法时常难以奏效;工频干扰奇次谐波的幅值随着频率的增大而骤减,在时间域难以准确识别,因此时间域编辑法效果不佳;此外,由于干扰源是固定的,工频干扰通常存在于整个采集过程中,通过数据段筛选也无法去除噪声。本文基于频域稀疏分解,先对采集的大地电磁信号进行傅里叶变换。然后设计与干扰信号相匹配而对有用信号不敏感的冗余字典原子,结合IOMP算法分离出频域信号中的工频干扰成分。最后将处理后的频域信号进行傅里叶逆变换。仿真实验及案例分析表明,所述方法能够在较好地保留有用信号的前提下有效压制工频干扰,在大大降低时间消耗的基础上取得比时域稀疏分解更好的效果,改善大地电磁数据质量。
Power-line interference is one of the most common noises in magnetotelluric(MT) data. It usually causes distortion at the fundamental frequency and its odd harmonics, and may also affect other frequency bands. Although trap circuits are designed to suppress such noise in most of the modern acquisition devices, strong interferences are still found in MT data, and the power-line interference will fluctuate with the changing of load current. The fixed trap circuits often fail to deal with it. This paper proposes an alternative scheme for power-line interference removal based on frequency-domain sparse decomposition. Firstly, the fast Fourier transform of the acquired MT signal is performed.Subsequently, a redundant dictionary is designed to match with the power-line interference which is insensitive to the useful signal. Power-line interference is separated by using the dictionary and a signal reconstruction algorithm of compressive sensing called improved orthogonal matching pursuit(IOMP). Finally, the frequency domain data are switched back to the time domain by the inverse fast Fourier transform. Simulation experiments and real data examples from Lu-Zong ore district illustrate that this scheme can effectively suppress the power-line interference and significantly improve data quality. Compared with time domain sparse decomposition, this scheme takes less time consumption and acquires better results.
Power-line interference is one of the most common noises in magnetotelluric(MT) data. It usually causes distortion at the fundamental frequency and its odd harmonics, and may also affect other frequency bands. Although trap circuits are designed to suppress such noise in most of the modern acquisition devices, strong interferences are still found in MT data, and the power-line interference will fluctuate with the changing of load current. The fixed trap circuits often fail to deal with it. This paper proposes an alternative scheme for power-line interference removal based on frequency-domain sparse decomposition. Firstly, the fast Fourier transform of the acquired MT signal is performed.Subsequently, a redundant dictionary is designed to match with the power-line interference which is insensitive to the useful signal. Power-line interference is separated by using the dictionary and a signal reconstruction algorithm of compressive sensing called improved orthogonal matching pursuit(IOMP). Finally, the frequency domain data are switched back to the time domain by the inverse fast Fourier transform. Simulation experiments and real data examples from Lu-Zong ore district illustrate that this scheme can effectively suppress the power-line interference and significantly improve data quality. Compared with time domain sparse decomposition, this scheme takes less time consumption and acquires better results.
引文
[1]GARCIA X,JONES A G.A new methodology for the acquisition and processing of audio-magnetotelluric(AMT)data in the AMT dead band[J].Geophysics,2005,70(5):G119-G126.
[2]GARCIA X,JONES A G.Robust processing of magnetotelluric data in the AMT dead band using the continuous wavelet transform[J].Geophysics,2008,73(6):F223-F234.
[3]REN Zheng-yong,KALSCHEUER T,GREENHALGH S,MAURER H.A goal-oriented adaptive finite-element approach for plane wave 3-D electromagnetic modelling[J].Geophysical Journal International,2013,194(2):700-718.DOI:10.1093/gji/ggt154.
[4]REN Zheng-yong,CHEN Chao-jian,TANG Jing-tian,ZHOU Feng,CHEN Huang,QIU Le-wen,HU Shuang-gui.A new integral equation approach for 3D magnetotelluric modeling[J].Chinese J Geophys,2017,60(11):4506-4515.doi:10.6038/cjg20171134.(in Chinese)
[5]LI Guang,XIAO Xiao,TANG Jing-tian,LI Jin,ZHU Hui-jie,ZHOU Cong,YAN Fa-bao.Near-source noise suppression of AMT by compressive sensing and mathematical morphology filtering[J].Applied Geophysics,2017,14(4):581-589.DOI:10.1007/s11770-017-0645-6.
[6]BUTLER K E,RUSSELL R D.Subtraction of powerline harmonics from geophysical records[J].Geophysics,1993,58(6):898-903.
[7]TRAD D O,TRAVASSOS J M.Wavelet filtering of magnetotelluric data[J].Geophysics,2000,65(2):482-491.
[8]TANG Jing-tian,LI Guang,XIAO Xiao,LI Jin,ZHOU Cong,ZHU Hui-jie.Strong noise separation for magnetotelluric data based on a signal reconstruction algorithm of compressive sensing[J].Chinese J Geophys,2017,60(9):3642-3654.DOI:10.6038/cjg20170928.(in Chinese)
[9]COHEN M B,SAID R K,INAN U S.Mitigation of 50-60 Hz power line interference in geophysical data[J].Radio Science,2010,45:RS6002.DOI:10.1029/2010RS004420.
[10]TANG Jing-tian,LI Guang,ZHOU Cong,REN Zheng-yong,XIAO Xiao,LIU Zi-jie.Denoising AMT data based on dictionary learning[J].Chinese J Geophys,2018,61(9):3835-3850.DOI:10.6038/cjg2018L0376.(in Chinese)
[11]GAMBLE T D,GOUBAU W M,CLARKE J.Magnetotellurics with a remote magnetic reference[J].Geophysics,1979,44(1):53-68.
[12]NEUKIRCH M,GARCIA X.Nonstationary magnetotelluric data processing with instantaneous parameter[J].Journal of Geophysical Research:Solid Earth,2014,119(3):1634-1654.DOI:10.1002/2013JB010494.
[13]WECKMANN U,MAGUNIA A,RITTER O.Effective noise separation for magnetotelluric single site data processing using a frequency domain selection scheme[J].Geophysical Journal International,2005,161(3):635-652.
[14]CANDES E J,ROMBERG J,TAO T.Robust uncertainty principles:Exact signal reconstruction from highly incomplete frequency information[J].IEEE Transactions on Information Theory,2006,52(2):489-509.
[15]CANDES E J,TAO T.Near-optimal signal recovery from random projections:Universal encoding strategies?[J]IEEETransactions on Information Theory,2006,52(12):5406-5425.
[16]DONOHO D L.Compressed sensing[J].IEEE Transactions on Information Theory,2006,52(4):1289-1306.
[17]CANDES E J,WAKIN M B.An introduction to compressive sampling[J].Signal Processing Magazine,IEEE,2008,25(2):21-30.
[18]GUO Xiao-le,YANG Kun-de,SHI Yang,DUAN Rui.An underwater acoustic data compression method based on compressed sensing[J].Journal of Central South University,2016,23(8):1981-1989.DOI:10.1007/s11771-016-3255-1.
[19]CAI T T,WANG L.Orthogonal matching pursuit for sparse signal recovery with noise[J].IEEE Transactions on Information Theory,2011,57(7):4680-4688.
[20]HENNENFENT G,HERRMANN F J.Simply denoise:Wavefield reconstruction via jittered undersampling[J].Geophysics,2008,73(3):V19-V28.
[21]TANG Gang,MA Jian-wei.Application of total-variationbased curvelet shrinkage for three-dimensional seismic data denoising[J].Geoscience and Remote Sensing Letters,IEEE,2011,8(1):103-107.
[22]ZHANG Xin-peng,HU Niao-qing,HU Lei,CHEN Ling.Abearing fault diagnosis method based on sparse decomposition theory[J].Journal of Central South University,2016,23(8):1961-1969.DOI:10.1007/s11771-016-3253-3.
[23]WANG Xin-qing,ZHU Hui-jie,WANG Dong,LI Yan-feng.The diagnosis of rolling bearing based on the parameters of pulse atoms and degree of cyclostationarity[J].Journal of Vibroengineering,2013,15(3):1560-1575.
[24]ZHU Hui-jie,WANG Xin-qing,RUI Ting,LI Yan-feng,LIUTian-shuai.Implication of improved matching pursuit in de-noising for square wave[J].Journal of PLA University of Science and Technology:Natural Science Edition,2015,16(4):305-309.(in Chinese)
[25]GUO Hai-yan,YANG Zhen,ZHU Wei-ping.A new single-channel speech separation method based on sparse decomposition[J].Acta Electronica Sinica,2012,40(4):762-768.(in Chinese)
[26]JIN Jian,GU Yuan-tao,MEI Shun-liang.An introduction to compressive sampling and its applications[J].Journal of Electronics&Information Technology,2010,32(2):470-475.(in Chinese)
[27]DAI Wei,MILENKOVIC O.Subspace pursuit for compressive sensing signal reconstruction[J].IEEETransactions on Information Theory,2009,55(5):2230-2249.
[28]PATI Y C,REZAIIFAR R,KRISHNAPRASAD P S.Orthogonal matching pursuit:Recursive function approximation with applications to wavelet decomposition[C]//Signals,Systems and Computers,1993.1993Conference Record of the Twenty-seventh Asilomar Conference on.IEEE,1993:40-44.
[29]NEEDELL D,TROPP J A.CoSaMP:Iterative signal recovery from incomplete and inaccurate samples[J].Applied and Computational Harmonic Analysis,2009,26(3):301-321.
[30]NEEDELL D,VERSHYNIN R.Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit[J].IEEE Journal of Selected Topics in Signal Processing,2010,4(2):310-316.
[31]HUANG Hong-lin,MAKUR A.Backtracking-based matching pursuit method for sparse signal reconstruction[J].IEEE Signal Processing Letters,2011,18(7):391-394.
[32]DONOHO D L,TSAIG Y,DRORI I,STARCK J.Sparse solution of underdetermined systems of linear equations by stagewise orthogonal matching pursuit[J].IEEETransactions on Information Theory,2012,58(2):1094-1121.
[33]TROPP J A,GILBERT A C.Signal recovery from random measurements via orthogonal matching pursuit[J].IEEETransactions on Information Theory,2007,53(12):4655-4666.
[2]GARCIA X,JONES A G.Robust processing of magnetotelluric data in the AMT dead band using the continuous wavelet transform[J].Geophysics,2008,73(6):F223-F234.
[3]REN Zheng-yong,KALSCHEUER T,GREENHALGH S,MAURER H.A goal-oriented adaptive finite-element approach for plane wave 3-D electromagnetic modelling[J].Geophysical Journal International,2013,194(2):700-718.DOI:10.1093/gji/ggt154.
[4]REN Zheng-yong,CHEN Chao-jian,TANG Jing-tian,ZHOU Feng,CHEN Huang,QIU Le-wen,HU Shuang-gui.A new integral equation approach for 3D magnetotelluric modeling[J].Chinese J Geophys,2017,60(11):4506-4515.doi:10.6038/cjg20171134.(in Chinese)
[5]LI Guang,XIAO Xiao,TANG Jing-tian,LI Jin,ZHU Hui-jie,ZHOU Cong,YAN Fa-bao.Near-source noise suppression of AMT by compressive sensing and mathematical morphology filtering[J].Applied Geophysics,2017,14(4):581-589.DOI:10.1007/s11770-017-0645-6.
[6]BUTLER K E,RUSSELL R D.Subtraction of powerline harmonics from geophysical records[J].Geophysics,1993,58(6):898-903.
[7]TRAD D O,TRAVASSOS J M.Wavelet filtering of magnetotelluric data[J].Geophysics,2000,65(2):482-491.
[8]TANG Jing-tian,LI Guang,XIAO Xiao,LI Jin,ZHOU Cong,ZHU Hui-jie.Strong noise separation for magnetotelluric data based on a signal reconstruction algorithm of compressive sensing[J].Chinese J Geophys,2017,60(9):3642-3654.DOI:10.6038/cjg20170928.(in Chinese)
[9]COHEN M B,SAID R K,INAN U S.Mitigation of 50-60 Hz power line interference in geophysical data[J].Radio Science,2010,45:RS6002.DOI:10.1029/2010RS004420.
[10]TANG Jing-tian,LI Guang,ZHOU Cong,REN Zheng-yong,XIAO Xiao,LIU Zi-jie.Denoising AMT data based on dictionary learning[J].Chinese J Geophys,2018,61(9):3835-3850.DOI:10.6038/cjg2018L0376.(in Chinese)
[11]GAMBLE T D,GOUBAU W M,CLARKE J.Magnetotellurics with a remote magnetic reference[J].Geophysics,1979,44(1):53-68.
[12]NEUKIRCH M,GARCIA X.Nonstationary magnetotelluric data processing with instantaneous parameter[J].Journal of Geophysical Research:Solid Earth,2014,119(3):1634-1654.DOI:10.1002/2013JB010494.
[13]WECKMANN U,MAGUNIA A,RITTER O.Effective noise separation for magnetotelluric single site data processing using a frequency domain selection scheme[J].Geophysical Journal International,2005,161(3):635-652.
[14]CANDES E J,ROMBERG J,TAO T.Robust uncertainty principles:Exact signal reconstruction from highly incomplete frequency information[J].IEEE Transactions on Information Theory,2006,52(2):489-509.
[15]CANDES E J,TAO T.Near-optimal signal recovery from random projections:Universal encoding strategies?[J]IEEETransactions on Information Theory,2006,52(12):5406-5425.
[16]DONOHO D L.Compressed sensing[J].IEEE Transactions on Information Theory,2006,52(4):1289-1306.
[17]CANDES E J,WAKIN M B.An introduction to compressive sampling[J].Signal Processing Magazine,IEEE,2008,25(2):21-30.
[18]GUO Xiao-le,YANG Kun-de,SHI Yang,DUAN Rui.An underwater acoustic data compression method based on compressed sensing[J].Journal of Central South University,2016,23(8):1981-1989.DOI:10.1007/s11771-016-3255-1.
[19]CAI T T,WANG L.Orthogonal matching pursuit for sparse signal recovery with noise[J].IEEE Transactions on Information Theory,2011,57(7):4680-4688.
[20]HENNENFENT G,HERRMANN F J.Simply denoise:Wavefield reconstruction via jittered undersampling[J].Geophysics,2008,73(3):V19-V28.
[21]TANG Gang,MA Jian-wei.Application of total-variationbased curvelet shrinkage for three-dimensional seismic data denoising[J].Geoscience and Remote Sensing Letters,IEEE,2011,8(1):103-107.
[22]ZHANG Xin-peng,HU Niao-qing,HU Lei,CHEN Ling.Abearing fault diagnosis method based on sparse decomposition theory[J].Journal of Central South University,2016,23(8):1961-1969.DOI:10.1007/s11771-016-3253-3.
[23]WANG Xin-qing,ZHU Hui-jie,WANG Dong,LI Yan-feng.The diagnosis of rolling bearing based on the parameters of pulse atoms and degree of cyclostationarity[J].Journal of Vibroengineering,2013,15(3):1560-1575.
[24]ZHU Hui-jie,WANG Xin-qing,RUI Ting,LI Yan-feng,LIUTian-shuai.Implication of improved matching pursuit in de-noising for square wave[J].Journal of PLA University of Science and Technology:Natural Science Edition,2015,16(4):305-309.(in Chinese)
[25]GUO Hai-yan,YANG Zhen,ZHU Wei-ping.A new single-channel speech separation method based on sparse decomposition[J].Acta Electronica Sinica,2012,40(4):762-768.(in Chinese)
[26]JIN Jian,GU Yuan-tao,MEI Shun-liang.An introduction to compressive sampling and its applications[J].Journal of Electronics&Information Technology,2010,32(2):470-475.(in Chinese)
[27]DAI Wei,MILENKOVIC O.Subspace pursuit for compressive sensing signal reconstruction[J].IEEETransactions on Information Theory,2009,55(5):2230-2249.
[28]PATI Y C,REZAIIFAR R,KRISHNAPRASAD P S.Orthogonal matching pursuit:Recursive function approximation with applications to wavelet decomposition[C]//Signals,Systems and Computers,1993.1993Conference Record of the Twenty-seventh Asilomar Conference on.IEEE,1993:40-44.
[29]NEEDELL D,TROPP J A.CoSaMP:Iterative signal recovery from incomplete and inaccurate samples[J].Applied and Computational Harmonic Analysis,2009,26(3):301-321.
[30]NEEDELL D,VERSHYNIN R.Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit[J].IEEE Journal of Selected Topics in Signal Processing,2010,4(2):310-316.
[31]HUANG Hong-lin,MAKUR A.Backtracking-based matching pursuit method for sparse signal reconstruction[J].IEEE Signal Processing Letters,2011,18(7):391-394.
[32]DONOHO D L,TSAIG Y,DRORI I,STARCK J.Sparse solution of underdetermined systems of linear equations by stagewise orthogonal matching pursuit[J].IEEETransactions on Information Theory,2012,58(2):1094-1121.
[33]TROPP J A,GILBERT A C.Signal recovery from random measurements via orthogonal matching pursuit[J].IEEETransactions on Information Theory,2007,53(12):4655-4666.