重力固体潮理论值导数的封闭公式

本文基于计算重力固体潮理论值的天顶距法,通过严格的理论推导,给出了计算重力固体潮理论值的导数的封闭公式．     

基于HHT提取重力固体潮的地震前兆信息

Hilbert-Huang Transformation(HHT)是一种新的非线性信号处理方法(Huang,1998).通过HHT对信号进行经验模态分解(empirical mode decomposition,简称EMD),能有效地把各种频率成分以本征模态函数(intrinsic mode function,简称IMF)形式从中分离出来.再对IMF序列进行Hilbert变换,可得到包含时间、频率、振幅的三维离散时频谱.它提供了非常清晰的局部细节时频特征,适合于描述具非线性非平稳性变化特征的信号.     

重力固体潮理论值导数的封闭公式

本文基于计算重力固体潮理论值的天顶距法，通过严格的理论推导，给出了计算重力固体潮理论值的导数的封闭公式．     

负载于零漂上的低频非潮汐信息的提取

重力固体潮观测资料中的零漂项，从整体上看，在缓慢地变化着，本文以朔望月的一半作为时间长工，分段对零漂进行线性模拟，之后，再进一步消除长周期潮汐波对零漂的影响，提出了零漂的变化，这是一种低频非潮汐信息，它负载于零漂之上，可能含有地震前兆。     

大气潮对重力固体潮影响的研究

通过气压变化对重力观测的影响和大气潮对重力固体潮的负荷效应二方面的研究,得出将ＧＳ型重力仪置于密封装置,能使气压的影响降低１个数量级。     

用小波分析提取重力固体潮

地球固体潮观测对验证各种地球模型、研究地球内部构造具有重要意义,可为地震预报提供重要的参考依据.BBVS-120甚宽带地震计具有较低的自噪声水平,在低频端输出信号的频率很低,涵盖固体潮信息频带范围.本文提出:BBVS-120地震计输出信号中存在周日波、半日波和1/3日波的固体潮信号,利用小波分析,提取垂直分量中的重力固体潮信号,并作调和分析.     

基于Matlab GUI的全球重力固体潮可视化实现

阐明重力固体潮理论值计算原理,利用改进的计算新方法编写Matlab计算程序,采用Matlab中的GUI平台,对全球重力固体潮进行可视化实现,直观观察固体潮在地面的时空变化规律。通过输入时间和经纬度,确定采样间隔(秒采样、分钟采样、时采样),实现以下功能:(1)以图像和Excel形式,输出某一地区的重力固体潮理论值;(2)仿真未来24小时全球重力固体潮。     

北京地区重力固体潮观测的初步结果

本文报道了北京地区1977年10月10日至1978年5月3日的重力固体潮观测结果。得出北京地区主要潮波的振幅系数δ和相位滞后κ为: δ(O_1)=1.1639±0.0086,κ(O_1)=0.44°±0.42° δ(M_2)=1.1593±0.0027,κ(M_2)=-0.40°±0.13     

基于category5月球内部结构模型的月球重力固体潮理论值计算

在地球、太阳和其他行星的引潮力的作用下,月球表面上任一点重力值将产生周期性的变化称为月球重力固体潮理论值.研究月球重力固体潮有助于我们更好地了解月球的内部结构、地壳运动以及月球的演化过程,这也为登月任务和月球探测提供了重要的科学依据,帮助我们更好地探索和理解月球的特性和性质.本文阐明了月球重力固体潮形成原因,根据category5月球内部结构模型计算出月球重力潮汐因子,依据Newcomb理论,采用ELP2000-85解析星历和Eckhardt月球天平动模型,提出一个计算月球重力固体潮理论值的方法,选取Apollo11作为测站,以波形图的形式输出该测站一天、一个月、一年的月球重力固体潮理论值,并探索讨论月球重力固体潮与月震的关系.结果表明：该测站一天、一个月、一年的月球重力固体潮理论值,最大值分别为：-1309μGal、-1290μGal、-1277μGal;最小值分别为：-1343μGal、-2349μGal、-2349μGal;与地球重力固体潮(这里选择与Apollo11经度纬度相同的坐标作为测站相比),月球重力固体潮变化相对简单,但波动幅度较大;推测月球的重力固体潮与深源月震之间可...     

基于多通道奇异谱分析的GNSS坐标时间序列共模误差的提取

共模误差是区域连续GNSS网中存在的一种与时空相关的主要误差源.为了有效的剔除共模误差,提高坐标时间序列的精度,本文提出了利用多通道奇异谱分析（Multi-channel Singular Spectrum Analysis,MSSA）提取共模误差的新思路,并利用实验区域18个测站9年（2002年到2010年）的GPS坐标时间序列进行实验,分析了共模误差对时间序列的影响和测站噪声特性的影响,并对共模误差序列进行周期探测,结果显示：通过MSSA能够有效的剔除共模误差,提高坐标时间序列的精度.     

Improvement of Nakamura technique by singular spectrum analysis

In this work we investigate the application of the Singular Spectrum Analysis to improve Nakamura Technique. The SSA has a wide and multidisciplinary range of applications; it allows a time series to be decomposed into different components, e.g. the signal itself, as well as various noise components, which can be subsequently removed from the data. Removal of the minor component of the data can lead to significant improvements in the identification of the system. In this paper the use of SSA Technique allows to optimize the signal to noise ratio before computing the classical Nakamura spectral ratios. A number of typical applications are also presented.     

基于奇异谱分析的重磁位场分离方法

奇异谱分析是一种近年兴起的时间序列分析方法,它利用降秩原理实现信号分离.该方法将数据空间投影到不同特征的子空间中,并用奇异值来表征这些子空间的性质,最后通过截取奇异值实现数据的重构.重磁位场分离可以看成一种多信号叠加的分离问题.不同特征的重磁异常具有不同特征的奇异谱,这是奇异谱分析用于解决位场分离问题的应用基础.本文通过建立理论模型,分析重磁异常的奇异谱特征,得出适用于重磁位场分离的最优参数选择方法,并与传统方法进行比较.对比发现,无论是横向叠加模型、垂向叠加模型还是斜向叠加模型,奇异谱分析都具有很好的分离效果.最后,将奇异谱分析用于鄂东南某矿区的重力资料处理中,实现弱异常的识别和分离.

     

体应变潮汐观测资料信息提取与映震效果

根据体应变观测资料的特点, 研究了体应变观测资料的处理方法, 提出了在时间域分析的数学模型。在数学模型中, 将潮汐因子、气压系数、非潮汐应变速率和加速度一并考虑, 在资料处理结果中, 这些参数可同时取得。分别用时间域分析方法和频率域分析方法对观测数据进行了处理, 发现潮汐因子、气压系数、应变速率和加速度等参数在大同地震前均有大小不同、持续时间不等的异常, 这些参数可作为物理意义明确的地震中短期预测的指标。     

琼中台重力非潮汐变化气压与海潮负荷改正

本文对琼中台连续重力观测数据进行收集整理并处理,基于处理后的数据,进行了潮汐分析和非潮汐分析。潮汐分析采用VAV调和分析方法;非潮汐分析则分别进行了零漂改正、固体潮改正、气压改正和海潮改正。其中,零漂改正采用一般多项式拟合零漂的方法;气压改正采用VAV软件;海潮改正运用SPOTL程序,以NAO.99b潮汐模型计算了琼中台海潮负荷值。最终获得了改正后的琼中台重力非潮汐变化,结果表明琼中台的重力气压导纳值为-0.34×10^-8m/s²/mbar,气压改正幅度约为10×10^-8m/s²,海潮改正幅度约为5×10^-8m/s²。改正后,琼中台重力非潮汐变化数据,比仅进行零漂固体潮改正后的重力非潮汐变化数据中的潮汐信号更加微弱,说明进行海潮改正后的效果是明显的,该方法可进一步去除其中的潮汐信号。     

Singular spectrum analysis and forecasting of hydrological time series

The singular spectrum analysis (SSA) technique is applied to some hydrological univariate time series to assess its ability to uncover important information from those series, and also its forecast skill. The SSA is carried out on annual precipitation, monthly runoff, and hourly water temperature time series. Information is obtained by extracting important components or, when possible, the whole signal from the time series. The extracted components are then subject to forecast by the SSA algorithm. It is illustrated the SSA ability to extract a slowly varying component (i.e. the trend) from the precipitation time series, the trend and oscillatory components from the runoff time series, and the whole signal from the water temperature time series. The SSA was also able to accurately forecast the extracted components of these time series.     

Storage in confined aquifer: Spectral analysis of groundwater in responses to Earth tides and barometric effect

Dilatation of aquifer and associated water level fluctuation in groundwater well is known to be driven periodically from lunar, solar, or other tidal forces. Time‐dependent variables in groundwater system, such as water level, can be converted to power spectra in the frequency domain using Fourier transform to evaluate significant fluctuation. The major innovation of this research is to develop spectral representation in frequency domain for the groundwater system that the storage in confined aquifer can be determined considering dilatation affected by Earth tides and barometric effect. In order to verify applicability of the evolved method, time series of Earth tides and barograph are collected; aquifer storage is then determined inversely by selecting significant semidiurnal and diurnal components in spectra computation. It suggests that to discover groundwater storage using groundwater level with barograph and tidal potential of Earth in frequency domain becomes accessible and feasible.     

集成奇异谱分析和自回归滑动平均预测日本近海海平面变化

本文从日本沿岸选取了28个验潮站及联测的GPS站,利用奇异谱分析（Singular Spectrum Analysis,SSA）和SSA+自回归滑动平均（Auto Regression Moving Average,ARMA）方法预测了2014—2018年的近海海平面变化和地壳垂直变化.并用同时段的验潮及GPS的实际测量值进行验证,结果显示,SSA+ARMA预测的相对海平面精度为0.0357~0.0607 m,地壳垂直运动的精度为0.0049~0.0077 m,绝对海平面的精度为0.0433~0.0683 m,且三者SSA+ARMA的预测结果均优于只用SSA预测的结果.在此基础上本文利用SSA+ARMA预测了日本沿岸2019—2023年的近海绝对海平面变化,结果显示,2019—2023年的平均海面高较往年（2014—2018）升高0.0353 m,2003—2023年绝对海平面的变化率为0.0039 m·a^-1,预测结果较为理想.

     

集成奇异谱分析和自回归滑动平均预测日本近海海平面变化

本文从日本沿岸选取了28个验潮站及联测的GPS站,利用奇异谱分析（Singular Spectrum Analysis,SSA）和SSA+自回归滑动平均（Auto Regression Moving Average,ARMA）方法预测了2014—2018年的近海海平面变化和地壳垂直变化.并用同时段的验潮及GPS的实际测量值进行验证,结果显示,SSA+ARMA预测的相对海平面精度为0.0357~0.0607 m,地壳垂直运动的精度为0.0049~0.0077 m,绝对海平面的精度为0.0433~0.0683 m,且三者SSA+ARMA的预测结果均优于只用SSA预测的结果.在此基础上本文利用SSA+ARMA预测了日本沿岸2019—2023年的近海绝对海平面变化,结果显示,2019—2023年的平均海面高较往年（2014—2018）升高0.0353 m,2003—2023年绝对海平面的变化率为0.0039 m·a^-1,预测结果较为理想.     

Application of singular spectrum analysis to identify the degrading structure using deteriorating distributed element model

Reinforced concrete structure may exhibit significant inelastic hysteretic behavior when subject to strong earthquake excitation. To investigate such an inelastic behavior, in this study, a new system identification technique is applied by using the deteriorating distributed element (DDE) model to simulate the hysteretic behavior of a degrading structure. Through the advanced signal processing technique, the multiple singular spectrum analysis (SSA) and the nonlinear SSA, the recorded inelastic restoring force of a deteriorating structure can be decomposed into several independent additive components in its sequentially degrading order and with decreasing weight. With each decomposed hysteresis loop, the model parameters of the DDE model are identified. The evolutionary properties of the progressive stiffness degradation behavior of reinforced concrete structure can be observed from the identified model parameters. Finally, comparison on the physical properties of the identified DDE model with respect to the seismic response data of the deteriorating structure is also discussed. The result shows that the proposed identification technique can have a good estimation on the seismic behavior of the degrading structure. Copyright © 2012 John Wiley & Sons, Ltd.     

Evidence of short-term groundwater recharge signal propagation from the Andes to the central Atacama Desert: a singular spectrum analysis approach

The effect of pressure-driven groundwater recharge signal propagation in the Andean-Atacamenian environment is investigated by assessing a record of 15 years of water table fluctuations of an unconfined–confined aquifer system. Based on a singular spectrum analysis of water table time series, it is shown that, in the given case, groundwater levels in the central Atacama Desert are hydraulically controlled by two distant recharge areas associated with the Andes. The maximum observed range of the pressure signal propagation is ~50 km over an elevation difference of more than 3000 m at a lag of ~25 months. Several findings indicate that an often-cited study misinterpreted a water level rise at the same site as an in-situ alluvial fan recharge. Thus, the effect’s impact on groundwater dynamics in complex aquifer systems can easily be overlooked. Singular spectrum analysis could be of use to investigate pressure effects at hydrologically comparable sites.