希尔伯特—黄变换(HHT)在EH-4数据去噪处理中的应用  

Application of Hilbert-Huang transform in EH-4 data processing

作　　者：黄泽佼 徐子东 罗晗 黄远生 HUANG Ze-Jiao;XU Zi-Dong;LUO Han;HUANG Yuan-Sheng(The key Laboratory of Marine Geological Resources and Environment of Hainan Province,Haikou 570206,China;Hainan Investigation Institute of Hydrogeology and Engineering Geology,Haikou 571100,China)

机构地区：[1]海南省海洋地质资源与环境重点实验室,海南海口570206 [2]海南水文地质工程地质勘察院,海南海口571100

出　　处：《物探与化探》2022年第5期1232-1240,共9页Geophysical and Geochemical Exploration

摘　　要：工频噪声源于社会生产活动中产生的电磁噪声,常会造成视电阻率曲线病态或发散。为了提高数据处理与解释的精度,本文针对EH-4数据中常见的工频噪声,采用希尔伯特—黄变换进行去噪处理,通过对实际数据的时间序列处理分析可知,该方法利用数据自身的时间尺度特征自适应地分解信号,能够很好地去除工频噪声,为大地电磁信号的去噪提供了一条有效的路径。另外,本文还针对经验模态分解过程中产生严重的模态混叠及“端点效应”进行分析,运用聚合经验模态(EEMD)对仿真信号及实测数据的时间序列进行分解,有效地解决了模态混叠等问题。Industrial frequency noise comes from the electromagnetic noise produced in social activities, and it causes apparent resistivity curves to become pathological or divergent. To improve the accuracy of data processing and interpretation, this study used the Hilbert-Huang transform(HHT) to remove the common power frequency noise in EH-4 data. According to the time series processing and analysis results of measured data, this method can self-adaptively decompose signals according to the time-scale characteristics of the data and successfully remove the industrial frequency noise in the data, thus providing an effective way to remove the noise in magnetotelluric signals. In addition, this study also analyzed the serious modal aliasing and "end effect" occurring in the process of the empirical mode decomposition and decomposed simulation signals and the time series of measured data using the ensemble empirical mode decomposition(EEMD), effectively solving problems such as modal aliasing.

关 键 词：EH-4去噪 经验模态法(EMD) 希尔伯特—黄变换(HHT) 聚合经验模态(EEMD) 

分 类 号：P631[天文地球—地质矿产勘探]