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为解决模态混叠问题,将总体经验模态分解方法应用于水文时间序列的多尺度研究中.将白噪声加入原始序列,经过总体经验模态分解后得到固有模态函数,通过对结果进行显著性检验并最终得到水文时间序列主要振荡周期、中心频率、平均振幅等信息.通过对黄河三门峡水文站实测天然年径流序列进行分析,发现总体经验模态分解能够较好地解决模态混叠现象;同时与小波分析方法对比,该方法较之传统的经验模态分解具有更高的精度,能够应用于水文时间序列多尺度分析研究.
In order to solve the problem of modal aliasing, the general empirical mode decomposition method is applied to the multi-scale study of hydrological time series.When the white noise is added to the original sequence, the intrinsic mode function is obtained after the general empirical mode decomposition, And then get the information such as the main oscillation period, the center frequency and the average amplitude of the hydrological time series finally.Analysis of the natural annual runoff series measured by the Sanmenxia Hydrologic Station in the Yellow River shows that the general empirical mode decomposition can solve the problem of modal aliasing At the same time, compared with the wavelet analysis method, this method is more accurate than the traditional empirical mode decomposition and can be applied to the multi-scale analysis of hydrological time series.