吉林大学学报(地球科学版) ›› 2017, Vol. 47 ›› Issue (3): 874-883.doi: 10.13278/j.cnki.jjuese.201703301

• 地球探测与信息技术 • 上一篇    下一篇

基于组合滤波的矿集区大地电磁信号去噪

蔡剑华1, 肖晓2   

  1. 1. 湖南文理学院物理与电子科学学院, 湖南 常德 415000;
    2. 中南大学地球科学与信息物理学院, 长沙 410012
  • 收稿日期:2016-09-20 出版日期:2017-05-26 发布日期:2017-05-26
  • 作者简介:蔡剑华(1979-),男,副教授,博士,主要从事大地电磁数据处理研究,E-mail:cjh1021cjh@163.com
  • 基金资助:
    国家自然科学基金项目（41304098）；湖南省自然科学基金项目（2017JJ2192）；湖南省教育厅重点项目（16A146）

De-Noising of Magnetotelluric Signal in the Ore Concentration Area Based on Combination Filter

Cai Jianhua1, Xiao Xiao2   

  1. 1. College of Physics and Electronics, Hunan University of Arts and Science, Changde 415000, Hunan, China;
    2. School of Geosciences and Info-Physics, Central South University, Changsha 410012, China
  • Received:2016-09-20 Online:2017-05-26 Published:2017-05-26
  • Supported by:
    Supported by National Natural Science Foundation of China (41304098) Natural Science Foundation of Hunan Province (2017JJ2192) and Key Research Fund of Hunan Province Education Department (16A146)

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摘要： 针对矿集区大地电磁（MT）信号受环境噪声和人文噪声污染严重的问题，提出一种结合了经验模态分解（EMD）和数学形态学滤波的组合滤波方法，对矿集区大地电磁信号的时域信号进行滤波处理。介绍了方法原理和计算步骤，评估了该方法的去噪效果；在与小波变换去噪效果对比的基础上，用仿真实验验证了方法的可靠性，并对某矿集区的实测数据进行了去噪处理。结果表明，组合滤波方法充分利用了EMD多尺度分解及其可重构特性和数学形态学滤波方法的优点，在滤除噪声的同时为MT信号尽可能多地保留了有用信息。去噪后，估算的响应曲线方差减小到原来的一半，为进一步正确资料处理和地质解释提供了保障。

关键词: 经验模态分解, 数学形态学滤波, 自适应滤波, 大地电磁, 去噪, 矿集区

Abstract: Aiming at the problem that the magnetotelluric signal in the ore concentration is affected by the environmental noise and the human noise pollution, a combinatorial method based on the EMD and mathematical morphology filter is described for filtering of MT time-series. The principle and steps of the method are given, and the de-noising effect of this method is evaluated. Comparing with wavelet transform, the simulation test results proved the reliability of this method, and the field measurement data of a certain mine area is processed. The results show that the combined filtering method makes full use of the multi-scale decomposition and reconfigurable characteristic of EMD and the advantages of mathematical morphology filter. While filtering out the noise, the useful information is retained as much as possible for the MT signal. After de-noising, the variance of the response curve is reduced to 1/2, which provides a guarantee for the correct data processing and geological interpretation.

Key words: empirical mode decomposition(EMD), mathematical morphological filtering, adaptive filtering, magnetotelluric signal, de-noising, ore concentration area

中图分类号: 

  • P631.3
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