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 tr...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.展开更多
Electromagnetic signals may be a promising precursor to seismic activity which has been observed in many case studies in past decades.However,the correlation and causation between the electromagnetic signals and the s...Electromagnetic signals may be a promising precursor to seismic activity which has been observed in many case studies in past decades.However,the correlation and causation between the electromagnetic signals and the seismic activity are still unclear without intensive observation network.In order to find seismoelectromagnetic phenomenon,we deployed AETA(acoustic and electromagnetic testing all-in-one system),a high-density multi-component seismic monitoring system in the China Earthquake Science Experiment site(CESE,in Sichuan Province and Yunnan Province,China)and the capital circle(areas with a distance which is≤200 km from Beijing),to record electromagnetic and geo-acoustic data across 0.1 Hz−10 kHz.In the course of data collection,we discovered an electromagnetic waveform that occurs on a daily basis.Because the signal generally coincides with sunrise and sunset,we named this phenomenon the SRSS(Sunrise-Sunset)waveform.After conducting three statistical tests based on seismicity and SRSS,we determined that the SRSS waveform is roughly correlated with the onset of seismic activity.It generally occurs at the regions where seismicity occurs.This discovery might have significant implications with respect to the future of earthquake prediction.展开更多
基金Project(2014AA06A602)supported by the National High-Tech Research and Development Program of ChinaProjects(41404111,41304098)supported by the National Natural Science Foundation of ChinaProject(2015JJ3088)supported by the Natural Science Foundation of Hunan Province,China
文摘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.
基金Projects(KJYY20170721151955849,JCYJ20190808161401653)supported by Fundamental Research Grant from Shenzhen Science&Technology,China。
文摘Electromagnetic signals may be a promising precursor to seismic activity which has been observed in many case studies in past decades.However,the correlation and causation between the electromagnetic signals and the seismic activity are still unclear without intensive observation network.In order to find seismoelectromagnetic phenomenon,we deployed AETA(acoustic and electromagnetic testing all-in-one system),a high-density multi-component seismic monitoring system in the China Earthquake Science Experiment site(CESE,in Sichuan Province and Yunnan Province,China)and the capital circle(areas with a distance which is≤200 km from Beijing),to record electromagnetic and geo-acoustic data across 0.1 Hz−10 kHz.In the course of data collection,we discovered an electromagnetic waveform that occurs on a daily basis.Because the signal generally coincides with sunrise and sunset,we named this phenomenon the SRSS(Sunrise-Sunset)waveform.After conducting three statistical tests based on seismicity and SRSS,we determined that the SRSS waveform is roughly correlated with the onset of seismic activity.It generally occurs at the regions where seismicity occurs.This discovery might have significant implications with respect to the future of earthquake prediction.
