基于自适应非稳态相位校正的时频域多尺度全波形反演

本文提出非稳态相位校正时频域目标函数,通过缩小观测数据与模拟数据在波形相位上的差异来缓解全波形反演过程中对应波形匹配错位的问题（周波跳跃）.同时引入自适应相位校正因子,可以根据观测数据与模拟数据的差异来调整相位校正量的大小.在构建非稳态相位校正时频域全波形反演目标函数的基础上,利用链式法则详细推导了对应的伴随震源,并从理论上证明了该方法的可行性与优越性.数值测试过程中结合了低通滤波多尺度反演策略,进一步缓解全波形反演过程中的强非线性问题.缺失低频分量测试结果表明,利用自适应非稳态相位校正时频域多尺度全波形反演方法结合常规全波形反演方法在缺失7 Hz以下低频分量的地震数据中仍然能够得到高精度的反演结果.震源不准确测试结果表明,即使震源子波相位差异较大,利用非稳态相位校正方法仍然能够一定程度上缓解周波跳跃现象.测试结果综合证明了本文提出的方法在构建初始速度建模,缓解周波跳跃等方面具有一定的优势.

     

GNMF小波谱分离在地震勘探噪声压制中的应用

地震勘探资料噪声压制及信噪比提高是整个地震勘探信号处理过程中的重要任务,随着地震勘探深度的增加及其复杂性,人们对地震数据质量的要求越来越高.勘探环境的复杂化使得采集到的地震资料中有效信号被大量噪声淹没,无法清晰辨识,严重影响后续的数据处理与解释.小波去噪是地震勘探中常用且发展较成熟的一种方法,但是其涉及到的阈值函数选取问题一直令人困扰,虽然已有多种阈值函数被提出,但仍存在各自的缺陷.本文利用小波分解在时域及频域良好的信号细节体现特性,引入模式识别中的非负矩阵分解(NMF)谱分离思想,针对小波系数阈值优化问题,提出了一种小波域图非负矩阵分解(GNMF)消噪算法.该方法首先在小波分解基础上,利用GNMF算法实现小波分解系数谱中信号分量与噪声分量的谱分离,然后通过反变换重构各分离子谱对应的子信号,最后利用K均值聚类算法将得到的多个子信号划分为信号类及噪声类,最终得到重构信号及分离噪声.合成记录和实际地震资料的消噪结果验证了新方法在提高信号与噪声分离准确性和精度方面的有效性,同时新方法避免了阈值选取造成的噪声压制不理想或有效成分损失问题.与小波消噪结果的对比及数值分析也说明了新方法在噪声压制及有效成分保持方面的优势.     

基于小波变换的大尺度岩体结构微震监测信号去噪方法研究

为将小波去噪方法应用于大尺度岩体结构微震监测信号的去噪研究,首先在MATLAB环境下进行仿真,验证了使用Symlet6小波进行小波去噪的可行性;利用4种自适应阈值规则对含噪信号进行去噪对比,结果表明4种阈值去噪后的信号在均方差较小的情况下都极大地提高了信号的信噪比,有效地去除了噪声,对不同的含噪信号,无偏似然原则阈值去...     

Hilbert-Huang变换与ELF信号处理

Hilbert-Huang变换(HHT)是近年出现的一种自适应的非平稳、非线性信号处理方法,该方法迄今已在许多非线性、非平稳信号处理的研究领域得到了很好的应用.本文简要介绍了Hilbert-Huang变换的基本实现原理与算法基础,通过仿真信号验证了该方法的有效性,并以实际数据为例,探讨了它在极低频(ELF)信号处理及噪声压制方面的应用.利用Hilbert-Huang变换对ELF信号进行频率域滤波,可以对噪声进行有效压制,从而提取已知频率的电磁信号,极大地提高信号质量.     

基于S变换的软阈值滤波在深地震反射数据处理中的应用

深地震反射原始单炮数据是非平稳的弱能量反射信号, 信噪比较低. 如何提高信噪比一直是深地震反射数据前处理中的一大难题. S变换是一种适用于分析非平稳信号的时频变换方法. 同其他分析时变信号的方法相比, S变换的基本小波不必满足小波在时间域均值为零的容许性条件, 它的时频分辨率与分析信号的频率有关, 且其在时间域的积分可以得到傅里叶频谱,其反变换也简单. 因此, S变换容易表示深地震反射信号复杂的时频特性. 本文在S变换的基础上, 利用软阈值滤波方法对深地震反射数据进行处理, 实验结果表明, 该方法有效地提高了信噪比, 压制了有效频带范围内的混频干扰, 突出了弱反射信号, 使得波组信息更加丰富, 有利于连续追踪有效反射波组和识别薄地层, 特别是提高了深部Moho界面反射层位的分辨率, 为深地震反射剖面后续处理和准确解释奠定了基础.     

时频域相位滤波在远震接收函数噪声压制中的应用

宽频带地震观测数据中有效信号和干扰噪声经常发生混频效应,常规的频率域滤波方法很难将二者分离.地震波信号属于时变非平稳信号,时频分析方法能够同时得到地震波信号随着时间和频率变化的振幅和相位特征,S变换是其中较为高效的时频分析工具之一.本文以S变换为例,提出了基于相位叠加的时频域相位滤波方法.与传统叠加方法相比,相位叠加方法对强振幅不敏感,对波形一致性相当敏感,更加利于有效弱信号信息的检测.时频域相位滤波方法滤除与有效信号不相干的背景噪声,保留了相位一致的有效信号成分,显著提高了信噪比.运用理论合成的远震接收函数数据和实际的宽频带地震观测数据检验结果显示该方法较传统的带通滤波方法相比,即使在信噪较低且混频严重条件下,时频域相位滤波方法的滤波效果依然很明显,有助于识别能量较弱的有效信号.

     

基于经验模态分解及独立成分分析的微震信号降噪方法

针对微震信号具有高噪声、突变快、随机性强等特点,基于经验模态分解(EMD)及独立成分分析(ICA)提出一种微震信号降噪方法.首先,对含噪信号进行EMD分解,获得一系列按频率从高到低的内蕴模态函数(IMF),利用原信号与各IMF之间的互相关系数辨识出噪声与信号的分界,将分界之上的高频噪声滤除;其次,为有效去除分界IMF中的模态混叠噪声,基于ICA算法对分界IMF进行盲源分离,提取其中的微震有效信号,并将其与剩余的IMF累加重构,从而得到降噪后的微震信号;最后,利用快速傅里叶变换(FFT)时频谱对比分析降噪前后的信号特征,定性说明本文方法的有效性;引入信噪比和降噪后信号占原信号的能量百分比两个参数,定量说明本文方法能充分保留微震信号的瞬态非平稳特征,降噪效果明显.     

基于小波函数的地震动反应谱与峰值位移拟合方法

采用数值方法合成地震动时,除对反应谱拟合外,对峰值位移的拟合和天然地震动非平稳特性的模拟也具有重要的意义和工程应用前景.本文基于小波函数的拟合方法,提出了一种能够同时合成目标反应谱和峰值位移的地震动加速度时程.数值算例表明:该方法具有较快的收敛速度,可用较少的迭代运算实现对目标反应谱和目标峰值位移的较高精度拟合;相较于...     

井约束非稳态相位校正方法

在地震勘探资料处理中,子波的零相位化有助于提高地震资料的分辨率、改善叠加剖面的质量.常规的相位校正方法是利用测井合成记录对井旁地震记录进行相位估计,然后对整条剖面进行常相位校正,该方法没有考虑地震子波相位的非稳态性（相位随时间和空间变化）.虽然通过局部相似度方法利用最大方差模准则或包络最大相似度准则可以估计出随时间和空间变化的相位属性,但是由于零相位判别准则本身具有一定的局限性,因此精度有限.针对这一问题,本文在局部地震属性和局部平面波模型下,提出了一种井约束的非稳态相位校正方法,该方法不仅考虑了子波相位的非稳态性,而且充分利用了测井合成地震记录进行相位校正精度高的优点.理论模型和实际资料处理表明,本文方法可以有效实现信号的零相位化,有利于改善叠加效果,提高资料的分辨率.     

强震加速度记录的数据处理方法

本文用数值积分法,对RDZ1-12-66型自动触发电流计记录式强震仪的幅频响应失真进行校正。并采用高通数字滤波的方法,修正加速度图的零线.为此编制了计算机程序,绘制了修正后的加速度、速度和位移时程曲线.计算了修正前后加速度图的傅氏谱。同时,对这些结果加以讨论。 修正后的加速度图,精确地表示了仪器基本频带在0.09HZ和25HZ之间的绝对地面加速度。     

合肥中心台地电阻率地铁干扰分析与抑制处理

以隶属合肥中心台的大蜀山台和合肥形变台地电阻率观测数据为研究对象,从时域上揭示了受地铁运行干扰的基本特征,经分析发现地电阻率受地铁干扰影响最大的为与轨道走向一致的测向,与轨道走向垂直测向所受的干扰最小;分别利用小波包阈值去噪和夜间观测均值代替日均值2种方法,对存在尖峰和突变的地铁干扰数据进行分析和去噪,结果表明:合肥形变台利用小波包阈值抑制地铁干扰效果较好,重构后的信号不仅大幅降低了地铁干扰的幅度,还去除了日常干扰所带来的背景噪声,能够较好地反映其原始信号变化特征,而大蜀山台更适用于夜间观测均值代替日均值的方法,可以提高地电阻率观测精度。     

On engineering equivalent linear analysis of soils in the frequency domain

This study investigated the performance, in the frequency domain, of an engineering equivalent linear method that is widely used in soil dynamics. A stochastic linear method using an extended differential equation by Wen and Baber was employed as the base line for evaluation. Stationary responses of single-degree-of-freedom non-linear systems under filtered white noise from both approaches were compared. For both a smooth nearly elasto-plastic material and soils, the study found that the engineering equivalent linear analysis underestimated rms displacements, but provided good estimates of rms acceleration responses. Furthermore, the frequency response functions of acceleration from both approaches were close at all levels of response.     

Obtaining estimates of the low-frequency ‘fling’, instrument tilts and displacement timeseries using wavelet decomposition

This paper proposes a novel, wavelet-based algorithm, which by extracting the low-frequency fling makes it possible to automatically correct for baseline shift and re-integrate down to displacement. The algorithm applies a stationary-wavelet transform at a suitable level of decomposition to extract the low frequency fling model in the acceleration time histories. The low frequency, acceleration fling should be as close as possible to the theoretical type A model, which after correction leads to a pulse-type velocity and ramp-like displacement after first and second integration. The wavelet transform essentially decomposes the seismic record using maximally flat filters and these together with a de-noising scheme form the core of this approach, which is to extract the lower and higher frequency sub-band acceleration, velocity and displacement profiles and correct for baseline shift. The correction automatically selects one time point from the low-frequency sub-band and then zeros the acceleration baseline after the fling. This implies pure, translation without any instrument tilts. Estimates of instrument tilt angles are also obtainable from the wavelet transformed time history as well as estimates of signal-to-noise ratios. The acceleration data used in this study is from station TCU068 in the near-fault region of the Chi-Chi, Taiwan, earthquake of 20th September 1999.     

几种时频分析方法的比较和实际应用

地震信号往往是非线性非平稳的,时频分析技术能同时展示信号在时间域和频率域的局部化特征。本文研究4种时频分析方法:短时傅里叶变换(STFT)、小波变换、广义相似文献   

Simulation and generation of spectrum-compatible ground motions based on wavelet packet method

This paper deals with the problem of generating spectrum-compatible artificial accelerograms for seismic dynamic analysis of engineering projects. A wavelet-packet-based, two-step procedure for the issue is proposed. The first step is to generate acceleration time history that could account for temporal and frequency non-stationarities of recorded ground motions. The second step is to decompose it into a desired number of wavelet packet vectors with high frequency resolution and non-overlapping frequency contents. Then each wavelet packet vector is scaled suitably and iteratively for the response spectrum of the simulated accelerogram to fit a specified design spectrum. The advantages of this procedure are that it can simulate user-specified acceleration time history with only 6 input parameters and the adjusted accelerogram has similar characteristics to the recorded one. The proposed procedure has been illustrated by simulating and modifying acceleration time history that are compatible with two different design spectrums for nuclear power plants. In addition, iterative efficiency of the method is investigated by simulating and adjusting acceleration time history for 100 successive times. The maximum relative error of the 76 period control points can reach 6% or below. Results show that the proposed method is effective and practical to generate and find spectrum-compatible ground motions with both stochastic and deterministic aspects.     

Localization and de-noising seismic signals on SASW measurement by wavelet transform

SASW method is a nondestructive in situ testing method that is used to determine the dynamic properties of soil sites and pavement systems. Phase information and dispersion characteristics of a wave propagating through these systems have a significant role in the processing of recorded data. Inversion of the dispersive phase data provides information on the variation of shear-wave velocity with depth. However, in the case of sanded residual soil, it is not easy to produce the reliable phase spectrum curve. Due to natural noises and other human intervention in surface wave date generation deal with to reliable phase spectrum curve for sanded residual soil turn into the complex issue for geological scientist. In this paper, a time–frequency analysis based on complex Gaussian Derivative wavelet was applied to detect and localize all the events that are not identifiable by conventional signal processing methods. Then, the performance of discrete wavelet transform (DWT) in noise reduction of these recorded seismic signals was evaluated. Furthermore, in particular the influence of the decomposition level choice was investigated on efficiency of this process. This method is developed by various wavelet thresholding techniques which provide many options for controllable de-noising at each level of signal decomposition. Also, it obviates the need for high computation time compare with continuous wavelet transform. According to the results, the proposed method is powerful to visualize the interested spectrum range of seismic signals and to de-noise at low level decomposition.     

考虑脉冲参数随机性的近断层地震动降维建模

根据50组近断层脉冲型强震动记录,采用连续小波变换提取最强速度脉冲分量,建立最强速度脉冲峰值时刻的统计模型。对近断层地震动加速度高频分量的演变功率谱模型参数进行识别,并利用谱表示-随机函数方法实现了降维模拟,进而积分得到速度高频分量。对脉冲参数进行随机化处理,并采用改进Gabor小波模型随机模拟速度低频分量。将速度高频分量与低频分量叠加得到近断层地震动速度时程。数值算例表明,近断层地震动加速度代表性时程集合的幅值谱和反应谱均与实测记录拟合一致,验证了降维模拟方法的工程适用性。近断层脉冲型地震动的降维模拟与概率密度演化理论相结合,可实现工程结构的随机地震反应与抗震可靠性精细化分析。     

基于Hi-net速度记录计算地震反应谱

强震仪和测震仪均能记录地面运动,强震仪输出的加速度记录主要用于分析结构地震反应,测震仪输出的速度记录常用于确定地震信息.由于这2种记录均描述地面运动,且覆盖结构地震反应分析所需频带范围,速度记录能否用于计算结构地震反应引起了人们的关注.为分析开源Hi-net速度记录用于计算结构地震反应时的精度,作者选取同台记录的加速度...     

空间局部加权回归自适应TFPF

时频峰值滤波(TFPF)算法是一种非常有效的去噪方法.但是传统的TFPF采用的单一窗长,并且仅沿时间方向进行滤波,忽略了信号的空间信息,并且TFPF近似等效成一个时不变的低通滤波器,不能追踪快速变化的信号.针对这些问题,引入空间局部加权回归自适应TFPF (SLWR-ATFPF).鉴于随机噪声在各个位置的方向随机性,以及有效信号在各个位置的方向确定性,首先利用空间局部加权回归(SLWR),对含噪信号进行空间加权,从而使加权之后的信号包含空间信息.然后,再引入凸集和Viterbi的思想,对空间加权之后的信号进行自适应滤波.从而,完成时空域二维自适应滤波.将SLWR-ATFPF应用于合成记录和实际的共炮点记录,实验结果表明,改进的方法与原算法相比,能够在压制低信噪比(SNR)随机噪声的同时更好地保留有效信号.     

Applications of wavelet analysis to the investigation of the dynamic behaviour of geotechnical structures

Harmonic wavelet analysis is a tool that has been developed over the past 15 years for the analysis of non-stationary signals in the time–frequency domain. This paper discusses the use of this technique and its application to the problems of soil dynamics and earthquake engineering. Specific reference is made to the use of this technique in investigating the performance of liquefiable slopes in centrifuge model earthquakes and the investigation of earthquake accelerograms.

Harmonic wavelet analysis will be shown to be a versatile tool that can reveal information unavailable traditional time or frequency domain analysis.