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首页> 外文期刊>Acta geodynamica et geomaterialia >Wavelet decomposition in the earth's gravity field investigation
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Wavelet decomposition in the earth's gravity field investigation

机译:小波分解在地球重力场研究中的应用

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摘要

This paper presents the results of the application of wavelet decomposition to processing data from the GGP sites (The Global Geodynamics Project). The GGP is an international project within which the Earth's gravity field changes are recorded with high accuracy at a number of stations worldwide using superconducting gravimeters. Data with a 5-second sampling interval from Wettzell and Bad Homburg were used for the research. The wavelet transform enables the investigation of the temporal changes of the oscillation amplitudes or the decomposition of the time series for the analysis of the required frequencies. The wavelet decomposition was performed using the regular orthogonal symmetric Meyer wavelet. The research concerned data from an earthquake period recorded at various locations and a quiet period when the gravimeters worked without any disturbances. The decomposition was followed by the Fast Fourier Transform for signal frequency components and then by correlation analyses of corresponding frequency components (for periods from 10 to 60 000 seconds) for all sensor combinations, for the quiet and the earthquake periods separately. Frequency components defining long term changes for all sensor combinations, as well as combinations between two sensors at the same site for the quiet days are characterised by high correlation coefficients. For the time of the earthquake, the Wettzell site data proved strong correlation for all frequency components, while the Bad Homburg site data showed an unexpected decrease of correlation for the majority of frequency components. The authors also showed that wavelet decomposition can be a good method of data interpolation, especially from the time of earthquakes. Moreover, it is a very useful tool for filtering the data and removing the noises.
机译:本文介绍了将小波分解应用于处理来自GGP站点(全球地球动力学项目)的数据的结果。 GGP是一项国际项目,在该项目中,全球范围内的多个站点都使用超导重力仪以高精度记录了地球的重力场变化。来自Wettzell和Bad Homburg的采样间隔为5秒的数据用于研究。小波变换可以研究振荡幅度的时间变化或时间序列的分解,以分析所需的频率。小波分解是使用正则正交对称Meyer小波进行的。该研究涉及重力记录仪在没有任何干扰的情况下在不同位置记录的地震时期和安静时期的数据。分解之后,对信号频率分量进行快速傅立叶变换,然后对所有传感器组合(分别在静默和地震时期)对相应频率分量(从10到60 000秒的时间段)进行相关分析。定义所有传感器组合的长期变化的频率成分,以及在安静的日子中同一站点的两个传感器之间的组合的频率成分具有较高的相关系数。在地震发生期间,Wettzell站点数据证明了与所有频率分量的强相关性,而Bad Homburg站点数据显示出与大多数频率分量的相关性出乎意料的下降。作者还表明,小波分解可能是一种很好的数据插值方法,尤其是从地震发生时。此外,它是用于过滤数据和消除噪声的非常有用的工具。

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