本文選題：大地電磁測深 + 匹配追蹤法��； 參考：《中國地質(zhì)大學(xué)(北京)》2015年碩士論文

【摘要】：大地電磁測深法是近年來最成熟的電法勘探技術(shù)之一,是研究地質(zhì)電性構(gòu)造、礦產(chǎn)電法勘探以及工程電法勘探的重要手段。由于其頻帶寬信號(hào)弱,易受日益廣泛的自然人文環(huán)境噪聲的干擾,因此有效的壓制噪聲,提高大地電磁數(shù)據(jù)的信噪比,保證大地電磁數(shù)據(jù)質(zhì)量,始終是大地電磁數(shù)據(jù)采集與數(shù)據(jù)處理的核心問題。然而大地電磁信號(hào)具有非線性、非平穩(wěn)和非最小相位的特點(diǎn),不滿足Fourier變換的條件,因此為了大地電磁測深信號(hào)噪聲壓制引入了短時(shí)Fourier變換、小波變換、Hilbert-Huang變換以及S變換等方法進(jìn)行去噪,對(duì)時(shí)間域定位和頻率域做諸多改進(jìn)。本文引進(jìn)一種新的信號(hào)分解方法,匹配追蹤法,通過建立冗余的過完備波形原子庫,實(shí)現(xiàn)貪婪算法分解步驟,對(duì)大地電磁信號(hào)分解得到線性表出,并利用Wigner-Ville譜得到大地電磁信號(hào)的時(shí)頻分布圖,認(rèn)識(shí)大地電磁測深信號(hào)受強(qiáng)噪聲干擾的時(shí)頻譜特征,通過加載理論噪聲,理論信號(hào)以及噪聲在時(shí)頻圖上的特征,認(rèn)識(shí)噪聲分離的規(guī)律,并通過對(duì)表出原子的特征進(jìn)行分析來達(dá)到信噪分離,而最終達(dá)到大地電磁測深受強(qiáng)噪聲干擾信號(hào)去噪的目的。大地電磁測深信號(hào)噪聲干擾按照形態(tài)進(jìn)行分類,分為脈沖噪聲、諧波噪聲、三角噪聲、似充放電噪聲、階躍噪聲以及方波噪聲,為去噪提供含噪聲信號(hào)模型;介紹匹配追蹤基本理論,利用高斯窗函數(shù)尺度變換、時(shí)移、頻移和相位變化構(gòu)造Gabor過完備原子庫;采用貪婪算法把理論模型函數(shù)以及大地電磁測深模型信號(hào)分別加載不同種類噪聲,在過完備庫上分解并且重構(gòu),驗(yàn)證匹配追蹤法分解重構(gòu)能夠在忽略殘差的情況下恢復(fù)信號(hào),為信噪分離打下基礎(chǔ);引入Wigner-Ville分布對(duì)重構(gòu)信號(hào)進(jìn)行時(shí)頻譜分析認(rèn)識(shí)各種噪聲在時(shí)頻譜上的特征,為信噪分離提供依據(jù)。通過時(shí)頻譜分析理論模型函數(shù)加載噪聲以及大地電磁測深模型加載信號(hào)的處理取得的信噪分離規(guī)律,應(yīng)用于實(shí)際大地電磁測深數(shù)據(jù)受各類噪聲影響信號(hào)的去噪處理,為大地電磁測深信號(hào)的噪聲抑制提供新方法和思路。
[Abstract]:Magnetotelluric sounding (MT) is one of the most mature electrical exploration techniques in recent years. It is an important means to study geo-electric structure, mineral electrical exploration and engineering electrical exploration. Because the frequency band signal is weak and easily disturbed by the increasingly widespread natural and human environment noise, the noise is suppressed effectively, the signal-to-noise ratio of magnetotelluric data is improved, and the quality of magnetotelluric data is guaranteed. It is always the core problem of magnetotelluric data acquisition and data processing. However, magnetotelluric signals have the characteristics of nonlinear, non-stationary and non-minimum phase, which do not meet the Fourier transform condition. Therefore, a short-time Fourier transform is introduced to suppress the noise of magnetotelluric sounding signals. Wavelet transform Hilbert-Huang transform and S transform are used to de-noising and many improvements are made in time domain localization and frequency domain. In this paper, a new signal decomposition method, matching tracing method, is introduced. By establishing a redundant over complete waveform atomic library, the greedy algorithm is implemented to decompose the magnetotelluric signal, and a linear representation is obtained for the decomposition of the magnetotelluric signal. The time-frequency distribution diagram of magnetotelluric signal is obtained by using Wigner-Ville spectrum, and the time-frequency characteristic of magnetotelluric sounding signal disturbed by strong noise is recognized, and the characteristics of theoretical noise, theoretical signal and noise on time-frequency chart are loaded by loading theoretical noise, theoretical signal and noise. The law of noise separation is recognized, and the signal noise separation is achieved by analyzing the characteristics of the atoms. Finally, the purpose of de-noising the intensely noisy signals in magnetotelluric measurement is achieved. The noise interference of magnetotelluric sounding signal is classified into pulse noise, harmonic noise, triangular noise, quasi-charge-discharge noise, step noise and square wave noise. The basic theory of matching tracing is introduced. The Gabor over complete atomic library is constructed by using Gao Si window function scale transformation, time shift, frequency shift and phase change. The greedy algorithm is used to load the theoretical model function and magnetotelluric sounding model signal into different kinds of noise, decompose and reconstruct the signal on the over-complete database, and verify that the matching tracing method can recover the signal under the condition of neglecting the residual error. It provides the basis for the separation of signal and noise, and introduces the Wigner-Ville distribution to analyze the time spectrum of reconstructed signal to understand the characteristics of various noises in the time spectrum, which provides the basis for the separation of signal and noise. The signal and noise separation rules obtained from the signal processing of magnetotelluric sounding model and magnetotelluric sounding model are applied to the de-noising processing of the actual magnetotelluric sounding data affected by various kinds of noise, which is obtained by time-spectrum analysis theory model function loading noise and magnetotelluric sounding model loading signal processing. It provides a new method and train of thought for noise suppression of magnetotelluric sounding signal.
【學(xué)位授予單位】：中國地質(zhì)大學(xué)(北京)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：P631.325

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本文編號(hào)：1954693