Method for recognizing and separating magnetotelluric signal and noise

A technology of magnetotelluric and separation methods, which is applied in pattern recognition, character and pattern recognition, instruments, etc. in signals, and can solve the problem of blindness, degradation of magnetotelluric signal data quality, and influence on reliability and interpretability of magnetotelluric data And other issues

Active Publication Date: 2018-02-02
HUNAN NORMAL UNIVERSITY
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Problems solved by technology

However, the existing technology mainly uses the overall processing method to suppress noise, which is blind, which leads to the removal of strong interference and some u...

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  • Method for recognizing and separating magnetotelluric signal and noise
  • Method for recognizing and separating magnetotelluric signal and noise
  • Method for recognizing and separating magnetotelluric signal and noise

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Embodiment Construction

[0072] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0073] like figure 1 As shown, the present invention discloses a method for identification and separation of magnetotelluric signal and noise, comprising the following steps:

[0074] Step 1. Initialize parameters, divide the magnetotelluric signal time series into J segments at equal intervals, and perform mean value removal processing on each magnetotelluric signal segment;

[0075] Step 2. Perform optimized intrinsic time scale decomposition on each magnetotelluric signal segment x(t) after de-meaning processing, and obtain N rotation components PR with frequencies distributed from high to low n (t) and a residual component R with a monotonically changing trend N (t), where n=1,2,...,N;

[0076] Step 3. Extract the sample entropy and fuzzy entropy of the N rotation components obtained by decomposing the optimized intrinsic time scale of e...

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Abstract

The invention provides a method for recognizing and separating magnetotelluric signal and noise. Firstly, a magnetotelluric signal collected in a strong electromagnetic interference environment is equidistantly segmented, by optimizing inherent time-scale decomposition, each magnetotelluric signal segment is subjected to adaptive decomposition to obtain a rotational component, and a sample entropyand a fuzzy entropy of the rotational component are extracted. Then, the sample entropy and the fuzzy entropy are taken as joint feature parameters to carry out fuzzy C-means clustering, according tothe feature parameters and a clustering method, a measured magnetotelluric signal sequence is divided into two kinds including a useful signal and a strong interference signal. Finally, only a magnetotelluric signal segment which is recognized as the strong interference signal is subjected to noise suppression processing by using a wavelet threshold, and a reconstructed magnetotelluric signal isobtained after superposition. The method has high reliability.

Description

technical field [0001] The invention belongs to the technical field of magnetotelluric signal processing, in particular to a method for identifying and separating magnetotelluric signal noise. Background technique [0002] Magnetotelluric sounding is an important electromagnetic prospecting technology, in which the natural alternating electromagnetic field is used as the field source to collect magnetotelluric data by measuring the mutually orthogonal electric and magnetic fields on the surface. Due to the weak natural electromagnetic field signal and wide frequency band, the data collected in the field will inevitably be disturbed by various noises. Especially in the mine-intensive areas, factors such as dense population and wireless communication base stations seriously restrict the quality of magnetotelluric data, resulting in excessive distortion of the apparent resistivity-phase curve, which greatly affects the interpretability of the underground electrical structure an...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06F2218/04G06F2218/08G06F18/23
Inventor 李晋张贤燕欢蔡锦刘晓琼邬芳
Owner HUNAN NORMAL UNIVERSITY
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