共查询到19条相似文献，搜索用时 281 毫秒
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研究如何在白天观测地脉动存在人为振动干扰情况下准确计算卓越周期.选择一个场地进行连续24 h地脉动观测.应用快速傅里叶变换计算地脉动数据的功率谱,应用Hilbert-Huang变换对地脉动数据进行经验模态分解并计算边际谱.通过实验发现,夜间和白天观测地脉动功率谱具有明显差异.在夜间观测的地脉动主峰明显,容易识别卓越周期,在白天观测的地脉动功率谱存在多个峰值,难以识别卓越周期.边际谱与功率谱基本一致,存在多个峰值,难以由边际谱判别卓越周期.通过实验还发现,可以由某一IMF分量的频谱判别卓越周期,但具体为哪个IMF分量需结合场地条件判断.对原始数据减去IMF分量后差值的频谱分析发现主峰明显,频率和夜间观测的非常接近,可以判别卓越周期.实验结果表明,对于在白天观测存在人为振动干扰的场地,难以通过功率谱和边际谱判别卓越周期,可以应用Hilbert-Huang变换进行经验模态分解,由原始数据减去IMF分量后差值的频谱峰值判别卓越周期. 相似文献
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采用四阶基数B-样条小波模拟地震动加速度时程,进而建立一种求地震反应的通用方法,解的误差仅来自于对地震动加速度时程的模拟。并用小波分解,将地震波分解为不同周期成分之和,以各分量最大加速度值的大小来衡量其在原波中的比重,可以清楚看到距震中不同远近地震波的性态,并做定量分析和观察各分量卓越周期的变化。求地震波及各分量的反应谱,从各分量的标准加速度反应谱中,可以看到地震波不同周期分量对体系固有周期的影响,这是以往做不到的。将上述方法应用于汶川8.0级地震加速度记录,研究不同地震记录的性态。 相似文献
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地震作用下黄土场地对地震波不同分量的放大效应影响显著。针对黄土高原典型黄土场地在地震作用下的放大效应,设计并完成大型地震模拟振动台试验,通过输入不同强度的地震动荷载,研究黄土场地加速度（PGA）放大系数、傅里叶谱、加速度反应谱、H/V谱比与地震动强度和场地高度的变化规律,揭示地震波不同分量对黄土场地效应的影响。结果显示：黄土场地对地震波的水平分量具有明显的放大效应,对地震波垂直分量的放大效应影响较小;随着高程的增加,地震波水平分量PGA放大系数呈现非线性变化;随着地震动强度和高程的增加水平分量卓越频率的频段和幅值逐渐增加,卓越频率向低频偏移,放大倍数呈现出非线性特性。 相似文献
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2016年6月23日,河北张家口尚义县发生M 4.0地震,发震构造为尚义-平泉断裂。采用基于聚类经验模态分解（EEMD）的HHT计算方法,对尚义M4.0地震强震动记录进行EEMD分解、Hilbert谱变换及谱分析,得到强震动台站的加速度记录分量的时程、FFT谱和边际谱、瞬时能量谱及时频谱,对比分析并认识各种谱的时频特性及规律,做好灾前预防工作,以减少人民生命财产损失。 相似文献
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本文旨在分析脉冲型地震动中不同频率的地震动分量对于原始地震动幅值及其非弹性反应谱的影响.首先以近期12次大地震的53条典型脉冲型地震动为数据基础,基于多尺度分解方法获取脉冲型地震动中的高频分量和低频分量.为与传统方法对比,本文获取了能够表征地震动脉冲特性的卓越分量及滤除卓越分量的剩余分量.然后对比分析原始地震动和4种地震动分量的幅值特征和非弹性反应谱的特性,以讨论地震动分量对原始地震动幅值参数及其非弹性反应谱的影响.最后结合简谐地震动模型和地震动分量的性质,讨论脉冲型地震动非弹性反应谱诸多特征的产生原因.分析发现,低频分量不仅是控制脉冲型地震动速度和位移幅值的主要因素,其对原始地震动的加速度幅值也具有不可忽略的影响.低频分量也是导致脉冲型地震动非弹性位移比谱偏大以及强度折减系数谱偏小的直接原因,从而造成结构在脉冲型地震动作用下需要具有更大的非弹性位移以及更高的强度需求. 相似文献
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基于小波变换的拟合规范反应谱多维地震动模拟 总被引：1，自引：0，他引：1
本文提出一种基于小波变换的拟合规范反应谱的多维地震动模拟算法。首先将规范反应谱推广到三维相关设计反应谱,然后将已有的三维地震动加速度时间历程曲线分解为一系列不同频段上的地震动分量,调整每一个地震动分量的幅值使其在相应的频率范围内拟合设计反应谱,最后经过调整后的地震动分量进行重构得到更新的地震动时间历程曲线。将该时间历程曲线的反应谱与目标反应谱进行比较,重复该过程直到误差位于特定的范围内。该方法可以保留原始地震动的局部时-频特性,为多维地震动的模拟提供了一种新的方法。 相似文献
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经验模态分解(Empirical Mode Decomposition, EMD)是一种具有较大应用潜力的去噪算法.目前,该算法存在的一个较大问题是过渡内蕴模态函数(Intrinsic Mode Function, IMF)中混叠噪声不能有效处理.过渡内蕴模态函数中混叠噪声不易剔除,限制了该算法的应用.本文针对此问题,通过研究过渡IMF的特点,首次提出一种有效去除过渡IMF中混叠噪声的方法.该方法首先对原信号进行一次EMD处理,得到包含过渡IMF的初步去噪结果,并将其与合适的余弦信号结合,改变其包络分布,然后对其结果再次进行EMD处理,仿真实验表明该方法在保留有效信号的同时,可以有效的去除过渡IMF中混叠的噪声,并将该方法用于实际地震资料随机噪声压制,处理效果令人满意. 相似文献
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Hilbert spectrum and intrinsic oscillation mode of dynamic response of a bilinear SDOF system： influence of harmonic excitation amplitude 总被引：1，自引：0，他引：1
Under harmonic wave excitation, the dynamic response of a bilinear SDOF system can be expressed by the Hilbert spectrum. The Hilbert spectrum can be formulated by (1) the inter-wave combination mechanism between the steady response and the transient response when the system behaves linearly, or (2) the intra-wave modulation mechanism embedded in one intrinsic mode function (IMF) component when the system behaves nonlinearly. The temporal variation of the instantaneous frequency of the IMF component is consistent with the system nonlinear behavior of yielding and unloading. As a thorough study of this fundamental structural dynamics problem, this article investigates the influence of the amplitude of the harmonic wave excitation on the Hilbert spectrum and the intrinsic oscillatory mode of the dynamic response of a bilinear SDOF system. 相似文献
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Due to strong heterogeneity of marine carbonate reservoir, seismic signals become more complex, thus, it is very difficult for hydrocarbon detection. In hydrocarbon reservoir, there usually exist some changes in seismic wave energy and frequency. In their instantaneous spectrums there often exist such phenomena that show the characteristics of attenuation of high frequency energy and enhancement of low-frequency energy. The three EMD-based time-frequency analysis methods' instantaneous spectra all have certain oil and gas detection capability. In this paper, we introduced the Normalized Hilbert Transform (NHT) and a new method named the HU method for hydrocarbon detection. The model results in the Jingbian Gas Field which is located in the eastern Ordos Basin, China, show that NHT and HU methods can be adopted. They also detect the gas-bearing reservoir efficiently as the HHT method does. The three EMD-based methods, that is, the Hilbert–Huang transformation (HHT) and NHT and HU methods, were respectively applied to analyze the seismic data from the Jingbian Gas Field. Firstly, the seismic signals were decomposed into a finite number of intrinsic mode functions (IMFs) by empirical mode decomposition (EMD) method. The second IMF signal (IMF2) of the original seismic section better indicates the distribution of the reservoir. Information on hydrocarbon-bearing reservoir is mainly in IMF2. Secondly, the HHT, NHT and HU methods were respectively used to obtain different frequency division sections from IMF2. Hydrocarbon detection was realized from the energy distribution of the different frequency division sections with these three EMD-based methods. The practical application results show that the three EMD-based methods can all be employed to hydrocarbon detection. Frequency division section of IMF2 using NHT method was better for the seismic data from the Jingbian Gas Field than when using the HHT method and HU method. 相似文献
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基于混合时频分析技术的地震数据噪声压制(英文) 总被引：2，自引：2，他引：0
针对复杂地质结构、陡倾角相干噪声、空间采样不均匀等情况下F-x域反褶积去噪技术的不足,提出首先应用具有时-频聚集性度量准则的广义S变换将时间-空间域的地震数据变换至时间-频率-空间域(t-f-x)的数据,在t-f-x域中对每一个频率切片应用经验模态分解(EMD),移除噪声占主导地位的本征模态函数以压制相干和随机噪声的滤波方法。模型分析表明第一本征模态函数表征的高频信息以噪声为主,移除第一本证模态函数可以达到压制噪声的目的。经广义S变换后形成t-f-x域中EMD滤波方法等效于具有依赖于空间位置、频率、高波数截断特征的自适应f-k滤波。此滤波方法考虑了数据的局部时-频特征,且具有执行简单的特点。与AR预测滤波方法比较,此法滤除的成分包含较少的低波数的信息,滤除的成分非常的局部化,且获得结果没有表现出过度平滑的特征。实际资料的应用表明在经广义S变换后形成t-f-x域中运用EMD滤波方法能够有效地压制随机和陡倾角相干噪声。 相似文献
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Hilbert-Huang变换在提取地震信号动力特性中的应用 总被引：1，自引：0，他引：1
H ilbert-Huang变换(HHT)是一种处理非线性、非平稳信号的新方法。它通过经验模态分解将信号分解为有限个固有模态函数,并对每个固有模态函数进行H ilbert变换得到H ilbert谱。本文将这种方法应用于地震信号动力特性的提取,有效地获得了信号能量的时频分布,量化提取了中心频率、瞬时相位、瞬时能量、H ilbert能量、最大振幅对应的时频分布等动力特性,并与Fourier变换、小波变换等进行了比较,显示了HHT的优势以及对于进一步实现结构分析和控制的重要意义。 相似文献
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E. A. ROBINSON 《Geophysical Prospecting》1975,23(4):779-797
Dynamic predictive deconvolution makes use of an entire seismic trace including all primary and multiple reflections to yield an approximation to the subsurface structure. We consider plane-wave motion at normal incidence in an horizontally layered system sandwiched between the air and the basement rock. Energy degradation effects are neglected so that the layered system represents a lossless system in which energy is lost only by net transmission downward into the basement or net reflection upward into the air; there is no internal loss of energy by absorption within the layers. The layered system is frequency selective in that the energy from a surface input is divided between that energy which is accepted over time by net transmission downward into the basement and the remaining energy that is rejected over time by net reflection upward into the air. Thus the energy from a downgoing unit spike at the surface as input is divided between the wave transmitted by the layered system into the basement and the wave reflected by the layered system into the air. This reflected wave is the observed seismic trace resulting from the unit spike input. From surface measurements we can compute both the input energy spectrum, which by assumption is unity, and the reflection energy spectrum, which is the energy spectrum of the trace. But, by the conservation of energy, the input energy spectrum is equal to the sum of the reflection energy spectrum and the transmission energy spectrum. Thus we can compute the transmission energy spectrum as the difference of the input energy spectrum and the reflection energy spectrum. Furthermore, we know that the layered system acts as a pure feedback system in producing the transmitted wave, from which it follows that the transmitted wave is minimum-delay. Hence from the computed energy spectrum of the transmitted wave we can compute the prediction-error operator that contracts the transmitted wave to a spike. We also know that the layered system acts as a system with both a feedback component and a feed-forward component in producing the reflected wave, that is, the observed seismic trace. Moreover, this feedback component is identical to the pure feedback system that produces the transmitted wave. Thus, we can deconvolve the observed seismic trace by the prediction-error operator computed above; the result of the deconvolution is the wave-form due to the feedforward component alone. Now the feedforward component represents the wanted dynamic structure of the layered system whereas the feedback component represents the unwanted reverberatory effects of the layered system. Because this deconvolution process yields the wanted dynamic structure and destroys the unwanted reverberatory effects, we call the process dynamic predictive deconvolution. The resulting feedforward waveform in itself represents an approximation to the subsurface structure; a further decomposition yields the reflection coefficients of the interfaces separating the layers. In this work we do not make the assumption as is commonly done that the surface as a perfect reflector; that is, we do not assume that the surface reflection coefficient has magnitude unity. 相似文献
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基于EMD与关联维的储层识别(英文) 总被引：1，自引：1，他引：0
在储层发育带,通常地震波波形会变复杂,所以关联维会变小。但由于地震波是有一定带宽的信号,波形受这个带宽内所有频率成分的影响,如果直接进行关联维的计算,其结果往往不能很好地反映储层。鉴于这种情况,提出了经验模态分解（EMD）与关联维相结合的方法,利用EMD对地震波进行分解,对分解后的每一个平稳的固有模函数（Intrinsic ModeFunction,IMF）分量进行关联维计算,将计算结果与有效的IMF分量进行储层预测。利用该方法对xx区三叠系中油组进行了试算,取得了较好的效果。 相似文献