基于希尔伯特-黄变换的九寨沟M7.0地震加速度记录时频分析
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摘要
2017年8月8日四川九寨沟M7.0地震是继2008年汶川M8.0地震和2013年芦山M7.0地震之后,青藏高原东缘在不到10年的时间内发生的第3个震级M7.0以上的强震,震中位于青藏高原巴颜喀拉块体东缘东昆仑断裂带东端的塔藏断裂、岷江断裂和虎牙断裂交汇部位,四川省地震局的数字强震台网共有37个台站获取了主震的三分量强震加速度记录。由于傅里叶(Fourier)变换仅能提供强震记录的频域信息,故本文在对九寨沟M7.0地震的加速度记录进行时频分析时采用了一种基于聚类经验模态分解(EEMD)的希尔伯特-黄变换(HHT)方法提取信号时频特性,通过对震中附近台站的加速度记录进行EEMD分解和希尔伯特(Hilbert)变换及谱分析,最终有效获得了信号能量的时频分布特征,量化提取了中心频率、Hilbert能量、最大振幅对应的时间等特性,并与Fourier变换进行了对比研究。研究结果表明:对于非线性的强震记录采用EEMD能够有效抑制经验模态分解(EMD)中存在的模态混叠问题,FFT谱与Hilbert边际谱相比,它在低频处会低估地震动的幅值,随着频率的增加,FFT谱又会放大其幅值。
On 8 August 2017,the Jiuzhaigou M7.0 earthquake following the Wenchuan M8.0 earthquake and the Lunshan M7.0 earthquake was the third strong shock in the past 10 years in the eastern margin of the Qinghai-Tibetan Plateau. The Jiuzhaigou earthquake occurred in the intersection area among the Tazang,Minjiang and Huya faults in the eastern part of the Bayan Har block of the Qinghai-Tibet Plateau. In this paper,Time-frequency characteristics of the method is used based on EEMD decomposition extraction signal in the treatment of the Jiuzhaigou M7.0 earthquake records. Through EEMD decomposition,Hilbert transform,and spectral analysis on the acceleration records of stations near the epicenter,the time-frequency distribution characteristics of the signal are effectively obtained.The characteristics of the center frequency,Hilbert energy,and maximum amplitude are extracted quantitatively. And a comparative study between the Fourier transform and wavelet transform was made.The study shows that for the non-linear strong earthquake records,EEMD can be used to inhibit the existing problem of mode mixing of EMD decomposition. In low frequency,the amplitude of ground motion is underestimated. With the increase of frequency,FFT spectrum will magnify the amplitude.
On 8 August 2017,the Jiuzhaigou M7.0 earthquake following the Wenchuan M8.0 earthquake and the Lunshan M7.0 earthquake was the third strong shock in the past 10 years in the eastern margin of the Qinghai-Tibetan Plateau. The Jiuzhaigou earthquake occurred in the intersection area among the Tazang,Minjiang and Huya faults in the eastern part of the Bayan Har block of the Qinghai-Tibet Plateau. In this paper,Time-frequency characteristics of the method is used based on EEMD decomposition extraction signal in the treatment of the Jiuzhaigou M7.0 earthquake records. Through EEMD decomposition,Hilbert transform,and spectral analysis on the acceleration records of stations near the epicenter,the time-frequency distribution characteristics of the signal are effectively obtained.The characteristics of the center frequency,Hilbert energy,and maximum amplitude are extracted quantitatively. And a comparative study between the Fourier transform and wavelet transform was made.The study shows that for the non-linear strong earthquake records,EEMD can be used to inhibit the existing problem of mode mixing of EMD decomposition. In low frequency,the amplitude of ground motion is underestimated. With the increase of frequency,FFT spectrum will magnify the amplitude.
引文
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[2]李大虎,赖敏,何强,等.基于聚类经验模态分解(EEMD)的汶川M8.0强震动记录时频特性分析[J].地震学报,2012,34(3):350-362
[3]杨培杰,印兴耀,张广智.希尔伯特-黄变换地震信号时频分析与属性提取[J].地球物理学进展,2007,22(5):1585-1590
[4]刘希康,丁志峰,李媛,等. STFT与WVD在地震波时频分析中的应用[J].地震地磁观测与研究,2016,37(1):15-21
[5]钟佑明,秦树人,汤宝平.希尔伯特-黄变换中边际谱的研究[J].系统工程与电子技术,2004,26(9):1323-1326
[6]Hassan H. Empirical Mode Decomposition(EMD)of potential field data:Airborne gravity data as an example[C].SEG/Houston 2005 Annual Meeting,2005:704-706
[7]罗奇峰,石春香. Hilbert-Huang变换理论及其计算中的问题[J].同济大学学报:自然科学版, 2003,31(6):637-640
[8]Bradley M B,Camelia K. Application of the empirical mode decomposition and Hilbert-Huang transform to seismic reflection data[J].Geophysics,2007,72(2):H29-H37
[9]王祝文,刘菁华,聂春燕. Hilbert-Huang变换在提取阵列声波信号动力特性中的应用[J].地球物理学进展,2008,23(2):450-455
[10]周挚,山秀明,张立,等.基于HHT提取昆明、下关重力固体潮的地震前兆信息[J].地球物理学报,2008,51(3):836-844
[11]SongJG, ZhaoCX, LinSH, etal.DecompositionofseismicsignalbasedonHilbert-Huangtransform[C]//International Conference on Business Management and Electronic Information. IEEE,2011:813-816
[12]Zhou Y,Chen W,Gao J,et al. Application of Hilbert–Huang transform based instantaneous frequency to seismic reflection data[J].J. App. Geophys.,2012,82(7):68-74
[13]Krishna B T. Electrocardiogram signal and linear time–frequency transform[J].J. Inst. Eng.,2014,95(4):377-382
[14]WuZH, HuangNE.Ensembleempiricalmodedecomposition:Anoiseassisteddataanalysismethod[J].Adv. Ad. Data Anal.,2009,1(1):1-41
[15]Rilling G, Flandrin P, Gonc P, et a1. On empirical mode decomposition and its algorithM[C]. IEEE-EURASIP work-shop on nonlinear signal and image processing,NSIP-03,2003,1-5
[16]Wu Z, Huang N E. Ensemble empirical mode decomposition:A noise-assisted data analysis method[R]. Calverton:Center for Ocean-Land-Atmosphere Studies,2005
[17]Tsui P H,Chang C C,Chang C C,et al. An adaptive threshold filter for ultrasound signal rejection[J].Ultrasonics,2008,49(4):413-418