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1.
通过EMD方法将地震动分解成若干固有模态函数,提出了用固有模态函数的时变VARMA建模实现地震动仿真的思路。算例分析表明,该方法充分利用了固有模态函数的特性,解决了直接基于ARMA或VARMA模型建模的仿真方法所面临的模型判阶的难题,并可同时考虑地震动的强度和频率非平稳特性,使仿真地震动与实际地震动在能量时频分布特性上具有较好的一致性且样本统计性较好,弹性及弹塑性反应谱拟合精度较高。 相似文献
2.
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
3.
基于EMD的信号瞬时特征的小波分析方法 总被引：8，自引：1，他引：7
提出了一种基于EMD(Empirical Mode Decomposition)的信号瞬时特征的小波分析方法。用这种方法提取非平稳信号的瞬时频率和瞬时幅值分三个基本步骤：首先,用EMD把信号分解成IMF(Intrinsic Mode Function)分量;接着,对IMF分量进行小波分析,从小波系数的幅角函数中提取小波脊线;最后,从小波脊线中提取瞬时频率和瞬时幅值。通过对仿真信号的分析,验证了该方法能有效地分析非平稳信号。 相似文献
4.
阵列声波信号是典型的非线性、非平稳信号,其动力特性的量化提取对于进行地层结构构造分析提供了必要的基础资料.而Hilbert-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(EMD)将信号分解为有限个固有模态函数(IMF),并对每个固有模态函数进行Hilbert变换得到Hilbert谱.本文将这种方法应用于阵列声波信号动力特性的提取,有效地获得了信号能量的时频分布,瞬时能量、Hilbert能量、最大振幅对应的时频分布等动力特性,显示了HHT的优势以及对于进一步实现地层结构构造分析的重要意义. 相似文献
5.
基于Hilbert-Huang变换和随机子空间识别技术提出了两种土木工程结构的模态参数识别方法。方法一是基于Hilbert-Huang变换和自然激励技术,通过经验模态分解和Hilbert变换提取信号的瞬时特性,进而利用自然激励技术和模态分析的基本理论识别结构的模态参数;方法二是基于经验模态分解和随机子空间识别技术,通过经验模态分解对信号进行预处理,进而运用随机子空间识别方法处理得到的结构单阶模态响应以识别结构的模态参数。利用这两种方法,通过对一12层钢筋混凝土框架模型振动台试验测点加速度记录的处理,识别了该模型结构的模态参数。识别结果与传统的基于傅里叶变换的识别结果及有限元分析结果的对比验证了这两种方法的可行性和实用性。 相似文献
6.
在简要介绍时程信号的小波分析和Hilbert-Huang变换(HHT)理论的基础上，通过地震波和其它时程信号实例，对比分析了小波变换和HHT变换结果. 比较显示:HHT变换和小波变换均能用于对非平稳的信号进行分析，并能捕捉到信号变化的主要特征；与受所选母波影响较大的小波分析不同，HHT变换得到的固有模态函数是直接从原始时程数据中分离出来的，它更能反映原始数据的固有特性；小波分析得到的谱的能量在频率范围内分布较广，而HHT变换的Hilbert谱的大部分能量都集中在一定的时间和频率范围内，能清晰地刻画信号能量随时间、频率的分布. 因此，Hilbert-Huang变换不仅是对非平稳信号进行分析的有效方法，而且也是检测时程信号局部特征的有用工具. 相似文献
7.
A method based on empirical-mode decomposition (EMD) and vector autoregressive moving average (VARMA) model is proposed for structural damage detection. The basic idea of the method is that the structural damages can be identified as the abrupt changes in energy distribution of structural responses at high frequencies. Using the time-varying VARMA model to represent the intrinsic mode functions (IMFs) obtained from the EMD of vibration signal, we define a damage index according to the VARMA coefficients. In the two examples given, the Imperial County Services Building and the Van Nuys hotel are used as the benchmark structures to verify the effectiveness and sensitivity of the damage index in real environments with the presence of actual noise. The analysis results show that the damage index can indicate the occurrence and relative severity of structural damages at multiple locations in an efficient manner. The damage index can also be potentially used for structural health monitoring, since it is based on the time-varying VARMA coefficients. Finally, some recommendations for future research are provided. 相似文献
8.
在2008年5月12日汶川MS8.0地震中,四川数字强震台网共获取了133组三分向加速度记录. 本文选取了一些不同断层距的台站所获取的强震动记录进行了处理和分析．在数据处理中,采用基于聚类经验模态分解（EEMD）提取信号时频特性的方法,有效获得了信号能量的时频分布,提取了中心频率、 Hilbert能量、最大振幅对应的时频等特性,并与傅里叶变换、小波变换进行了对比研究．研究结果表明, 对非线性的强震记录采用聚类经验模态分解（EEMD）能抑制经验模态分解（EMD）中存在的模态混叠问题;与傅里叶变换和小波变换相比发现, HHT边际谱在低频处幅值高于傅里叶谱;与小波变换受到所选取的母波强烈影响不同, HHT直接从强震记录中分离出固有模态函数（IMF）,更能反映出原始数据的固有特性, Hilbert谱反映出大部分能量都集中在一定的时间和频率范围内,而小波谱的能量却在频率范围内分布较为广泛．因此,基于EEMD的HHT在客观性和分辨率方面都具有明显的优越性,能提取到更多强震加速度记录的时频特性． 相似文献
9.
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
10.
地震信号属于非线性和非平稳信号,传统的分析方法主要包括短时傅立叶变换、小波变换和Cohen类时频分布等等;希尔伯特-黄变换是分析非平稳信号的新方法,该方法的关键部分是信号的经验模态分解,通过经验模态分解,复杂的信号可以分解为有限的数量很少的几个固有模态函数,从而可以得到信号的希尔伯特时频谱;将该方法应用于单个的地震道数据,可以对地震道进行经验模态分解并得到希尔伯特谱,应用于地震剖面,可以得到意义更加明确的瞬时频率和瞬时振幅等地震属性,模型试算和实际应用表明了该方法的有效性. 相似文献
11.
Structural modal parameter identification and damage diagnosis based on Hilbert-Huang transform 总被引：1，自引：1，他引：0
Traditional modal parameter identifi cation methods have many disadvantages,especially when used for processing nonlinear and non-stationary signals.In addition,they are usually not able to accurately identify the damping ratio and damage.In this study,methods based on the Hilbert-Huang transform(HHT) are investigated for structural modal parameter identifi cation and damage diagnosis.First,mirror extension and prediction via a radial basis function(RBF) neural network are used to restrain the troublesome end-effect issue in empirical mode decomposition(EMD),which is a crucial part of HHT.Then,the approaches based on HHT combined with other techniques,such as the random decrement technique(RDT),natural excitation technique(NExT) and stochastic subspace identifi cation(SSI),are proposed to identify modal parameters of structures.Furthermore,a damage diagnosis method based on the HHT is also proposed.Time-varying instantaneous frequency and instantaneous energy are used to identify the damage evolution of the structure.The relative amplitude of the Hilbert marginal spectrum is used to identify the damage location of the structure.Finally,acceleration records at gauge points from shaking table testing of a 12-story reinforced concrete frame model are taken to validate the proposed approaches.The results show that the proposed approaches based on HHT for modal parameter identifi cation and damage diagnosis are reliable and practical. 相似文献
12.
Empirical mode decomposition aims to decompose the input signal into a small number of components named intrinsic mode functions with slowly varying amplitudes and frequencies. In spite of its simplicity and usefulness, however, empirical mode decomposition lacks solid mathematical foundation. In this paper, we describe a method to extract the intrinsic mode functions of the input signal using non‐stationary Prony method. The proposed method captures the philosophy of the empirical mode decomposition but uses a different method to compute the intrinsic mode functions. Having the intrinsic mode functions obtained, we then compute the spectrum of the input signal using Hilbert transform. Synthetic and field data validate that the proposed method can correctly compute the spectrum of the input signal and could be used in seismic data analysis to facilitate interpretation. 相似文献
13.
Hilbert-Huang Transform(HHT)是一种新的适用于非线性、非平稳信号,且具有自适应性的数据处理方法．本文简要介绍了一座45层钢筋混凝土框架结构及其振动台试验模型概况. 利用HHT分析了模型结构在不同烈度地震中的反应记录,得到了Hilbert时频幅值三维分布和Hilbert边际谱．Hilbert谱得到记录能量集中分布的频段与时间范围,捕捉到信号变化的主要特征. Hilbert边际谱曲线形状和峰值频率值随着地震烈度的升级而发生了相应变化,而且所有的结果图形体现出相同的规律性,预示着Hilbert边际谱在土木工程结构安全评价中的应用前景． 相似文献
14.
Jian-hua Cai 《Pure and Applied Geophysics》2013,170(11):1899-1911
Magnetotelluric (MT) data series are non-stationary random signals that do not meet the basic requirements of conventional methods based on the Fourier transform. To minimize the estimation bias errors brought about by the non-stationary characteristics of MT data, a new method, based on the Hilbert–Huang transform (HHT), is proposed for the first time for estimating the MT response functions from a time series of electromagnetic field variations. With the HHT method, the amplitude of data series are expressed as a function of frequency and time and then response functions are estimated statistically from the time–frequency spectrum. Mathematical model and calculation processes are introduced and some simulated data are analyzed to verify the correctness of the method. Finally, the measured MT data is facilitated by applying the HHT to assess the ability of HHT method to quantify meaningful geologic information. 相似文献
15.
This study proposes a recording-based approach to characterize and quantify earthquake-induced site nonlinearity, exemplified as soil nonlinearity and/or liquefaction. Alternative to Fourier spectral analysis (FSA), the paper introduces time–frequency analysis of earthquake ground motion recordings with the aid of so-called Hilbert-Huang transform (HHT), and offers justification for the HHT in addressing the nonlinear features shown in the recordings. With the use of the 2001 Nisqually earthquake recordings, this study shows that the proposed approach is effective in characterizing site nonlinearity and quantifying the influences in seismic ground responses. Major results from this study are listed below.
- 1. HHT-based site amplification is defined as the ratio of marginal Hilbert amplitude spectra, similar to the Fourier-based one that is the ratio of Fourier amplitude spectra. The HHT-based site amplification can be used in effectively quantifying site nonlinearity in terms of frequency downshift in the low-frequency range and amplification-reduction factor in intermediate-frequency range in comparison with the Fourier-based one.
- 2. Instantaneous damping, and Hilbert and marginal Hilbert damping spectra are defined in ways similar to instantaneous frequency, and Hilbert and marginal Hilbert amplitude spectra, respectively. Consequently, the HHT-based site damping is found as the difference of marginal Hilbert damping spectra, which can be used as an alternative, complementary index to measure the influences of site nonlinearity in seismic ground responses.
Keywords: Site nonlinearity; Site amplification; Site damping; Hilbert-Huang transform (HHT); Liquefaction; 2001 Nisqually earthquake 相似文献
16.
建筑物在强震中可能受到损伤,通过对结构瞬时频率的分析可以诊断出结构的损伤发展过程。本文探讨了基于H ilbert-Huang变换的结构物损伤诊断方法,研究了如何从结构地震响应信号中提取模态响应、1阶模态振型和损伤发展规律。本文采用HHT法分析了Northridge地震中某超高层建筑物的强震记录,分析结果表明:带有间歇检验准则的经验模态分解法能够提取结构的模态振动响应;通过分析不同楼层的相对H ilbert边际谱能够识别出结构的1阶模态振型;分析结构振动中瞬时频率的时变特点,可以直观地掌握振动中结构的损伤发展规律。 相似文献
17.
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
18.
随掘地震超前探测震源具有连续、非可控的特点,需要使用互相关技术将连续震源记录转换为等效脉冲震源记录以获取有效反射信号。但随掘地震超前探测信号往往包含一些能量较强且频带较窄的优势频率成分,使得互相关处理会引入较严重的干扰。为此,本文提出将基于变分模态分解（VMD）的希尔伯特谱白化方法应用于随掘地震超前探测信号。该方法首先利用VMD将地震信号分解为若干个本征模态函数（IMF）,再对各IMF应用希尔伯特变换进行时频分解,最后使用白化滤波器对其希尔伯特谱进行谱白化。数值模拟结果表明基于VMD的希尔伯特谱白化方法能够在保持各道信号一致性的同时均衡信号的不同频率成分,有效压制互相关结果中的虚假同相轴,加快主峰旁瓣衰减。将本文方法应用于安徽淮北杨庄煤矿某巷道实际数据,成功探测了掌子面前方存在的断层构造,表明该方法具有较好的实用性。 相似文献
19.
希尔伯特—黄变换(Hilbert-Huang transform,HHT)是一种新的适合非平稳和非线性信号的分析方法,由于地震信号一般呈现出非平稳与非线性特性,因此HHT非常适合地震信号的分析。本文首先介绍了HHT中关于经验模态分解(Empirical Mode Decomposition,EMD)的实现过程,在此基础上分析了几种基于EMD获得本征模态函数(Intrinsic Mode Functions,IMF)来计算瞬时频率的算法,其中利用了两个采样间隔瞬时频率的平均来计算瞬时频率,较好地反映了地震信号频率成分随时间变化的特征。将该方法应用于四川东北部某地区海相碳酸盐岩地层三维地震叠后偏移数据处理,提取"三瞬"地震属性,与传统的希尔伯特变换提取的"三瞬"地震属性进行对比,结果表明基于HHT的"三瞬"地震属性结果具有更高的分辨率,IMF2的瞬时相位能够较好地刻画台地边缘生物礁相,IMF2的瞬时频率亦具有较好的分带性。将IMF2的"三瞬"地震属性与钻井等资料结合分析,能够更好地识别沉积相的分布。 相似文献
20.
HHT的滤波特性及在声波测井波列信号处理中的应用(英文) 总被引：2，自引：2，他引：0
阵列声波信号是典型的非线性、非平稳信号,Hilbert～Huang变换（HHT）是处理非平稳信号的一种比较新的时频分析方法。通过对信号进行经验模态分解（EMD）和对瞬时频率的求解,可以获得声波信号的时一频谱。其关键技术就是进行经验模态分解,任何非平稳的信号都可以分解为有限数目并且具有一定物理意义的固有模态函数。EMD方法可以理解为以声波信号极值特征尺度为度量的时频滤波过程。滤波器充分保留了声波信号本身的非线性和非平稳特征,在声波信号的滤波和去噪中具有很大的优势。文中介绍了HHT时频滤波的实现过程,并列举了一些声波测井波列实例,说明了该方法的有效性。 相似文献