青草沙水库工程的风险识别

青草沙水库工程属大型水利工程。工程在施工阶段和运行期间,均存在不确定性因素多、风险因素和风险事件发生概率大的特点。本文利用风险识别方法,对青草沙水库工程不同阶段的风险进行了识别。     

基于经验模态分解的形变信号滤波处理与异常提取

本文介绍了经验模态分解的方法与原理,给出了由经验模态分解产生的固有模态函数重构组合滤波器的原理与详细算法。通过对形变观测中典型干扰信号的综合处理、异常提取试验及其所取得的效果,综合分析认为,经验模态分解组合滤波器方法可作为形变观测数据处理中一种新的行之有效的分析方法。     

Relationship between land cover and monsoon interannual variations in east Asia

Asian monsoon have multiple forms of variations such as seasonal variation, intra-seasonal variation, interannual variation, etc. The interannual variations have not only yearly variations but also variations among several years. In general, the yearly variations are described with winter temperature and summer precipitation, and the variations among several years are reflected by circulation of ENSO events. In this study, at first, we analyze the relationship between land cover and interannual monsoon variations represented by precipitation changes using Singular Value Decomposition method based on the time series precipitation data and 8km NOAA AVHRR NDVI data covering 1982 to 1993 in east Asia. Furthermore, after confirmation and reclassification of ENSO events which are recognized as the strong signal of several year monsoon variation, using the same time series NDVI data during 1982 to 1993 in east Asia, we make a Principle Component Analysis and analyzed the correlation of the 7th component eigenvectors and Southern Oscillation Index (SOI) that indicates the characteristic of ENSO events, and summed up the temporal-spatial distribution features of east Asian land cover’s inter-annual variations that are being driven by changes of ENSO events.     

东亚土地覆盖动态与季风气侯年际变化的关系

以东亚地区 １９８２～１９８９年时间序列降水资料及 ＡＶＨＲＲ ８ ｋｍ ＮＤＶＩ数据为基本数据源，应用地理信息系统技术，分别研究了东亚地区夏季（５－９月）降水及土地覆盖的年际变化，并揭示了研究时间段内各自的变化规律。进一步用奇异值分解（ＳＶＤ）模型方法分析了以降水变化为表征的东亚地区气候年际变化与土地覆盖年际变化之间的关系。     

1993—2016年中国近海海平面时空变化趋势

区域海平面变化是目前气候变化研究的热点问题.海平面变化具有时间和空间的异质性,分析海平面变化,应充分考虑时间和空间的差异.基于集合经验模态分解(Ensemble Empirical Mode Decomposition,EEMD)、最小二乘法,利用卫星高度计、验潮站数据,分析了1993—2016年间中国近海及周边海域海...     

Coherency matrix-based proper orthogonal decomposition with application to wind field simulation

Proper Orthogonal Decomposition （POD） provides a powerful modal transformation tool for stochastic dynamics. In this paper, coherency matrix-based proper orthogonal decomposition （CPOD） is presented as an innovative form of the POD based on cross power spectral density matrices. By introducing a discretizing scheme, the CPOD-based spectral representation method is obtained for use in stochastic simulation. Moreover, some criteria are proposed that allow the truncation order of CPOD to be conveniently determined. A numerical example to illustrate the application of the proposed method for the simulation of a wind velocity field is provided.     

Earthquake‐induced structural response output‐only identification by two different Operational Modal Analysis techniques

Output‐only system identification is developed here towards assessing current modal dynamic properties of buildings under seismic excitation. Earthquake‐induced structural response signals are adopted as input channels for two different Operational Modal Analysis (OMA) techniques, namely, a refined Frequency Domain Decomposition (rFDD) algorithm and an improved Data‐Driven Stochastic Subspace Identification (SSI‐DATA) procedure. Despite that short‐duration, non‐stationary, earthquake‐induced structural response signals shall not fulfil traditional OMA assumptions, these implementations are specifically formulated to operate with seismic responses and simultaneous heavy damping (in terms of identification challenge), for a consistent estimation of natural frequencies, mode shapes, and modal damping ratios. A linear ten‐storey frame structure under a set of ten selected earthquake base‐excitation instances is numerically simulated, by comparing the results from the two identification methods. According to this study, best up‐to‐date, reinterpreted OMA techniques may effectively be used to characterize the current dynamic behaviour of buildings, thus allowing for potential Structural Health Monitoring approaches in the Earthquake Engineering range.     

集合经验模态分解(EEMD)在地下水位数据处理中的应用初探

使用集合经验模态分解方法将水位观测数据分为高、中、低等3个频率分量。高频分量可以用来识别和研究包含同震响应在内的高频事件;中间频率分量包含固体潮的半日波、全日波信号;低频分量则反映观测数据的长期趋势性变化特征。在此基础上,将该方法应用于张道口-1井和新10井的水位观测分钟值数据,从处理后得到的高频分量中识别出31次7级以上地震的同震响应,定量地分析了其最大振幅随震中距和震级的变化特征。     

Crop characterization using an improved scattering power decomposition technique for compact polarimetric SAR data

Crop characterization using Compact-Pol Synthetic Aperture Radar (CP-SAR) data is of prime interest with the rapid advancements of SAR systems towards operational applications. It is noteworthy that as a good compromise between the dual and quad-polarized SAR systems, the CP-SAR offer advantages in terms of the larger swath and lower data rate. The m − χ CP decomposition considers two out of the three Stokes child parameters: degree of polarization (m), ellipticity (χ), and orientation angle (ψ) to describe the polarized part of the quasi-monochromatic partially polarized wave. An improvement in the scattering powers was proposed in the S − Ω decomposition, which takes into accounts both the transmitted and received wave ellipticities (χ_t, χ_r) and the orientation angles (ψ_t, ψ_r). In this decomposition, S denotes the Stokes vector and Ω is the polarized power fraction. However, it may be noted that the S − Ω decomposition intrinsically ignores dominance in the target scattering mechanism while calculating the powers. In this work, improvement is proposed for the S − Ω decomposition by utilizing the degree of dominance in the scattering mechanism. The improved S − Ω (named as iS − Ω) decomposition powers are first compared with the existing m − χ and S − Ω powers for elementary (viz., trihedral and dihedral corner reflectors) and distributed targets using simulated CP-SAR data from quad-pol RADARSAT-2 data. An increase of ∼2% for odd and even-bounce powers obtained from the iS − Ω decomposition is observed for the trihedral and dihedral corner reflectors respectively. The analysis of the scattering powers for distributed targets shows that an increase of 15% and 12% in the even and odd-bounce powers is observed from iS − Ω for urban and bare soil areas respectively as compared to the m − χ and S − Ω decompositions. Besides, temporal variations in the scattering powers obtained from the iS − Ω decomposition are also analyzed for rice, cotton, and sugarcane crops at different growth stages.     

相位降噪与矢径分解组合的矢量序列分解方法

基于矢量序列相位与矢径的统计分布差异,本文提出一种TV (Total Variation)相位降噪和EMD (EmpiricalMode Decomposition)矢径分解组合的矢量序列降噪、分解方法。利用TV细致的演化特点进行相位降噪,其中引入最大信杂比准则,以优化选择调整参数和迭代次数;利用EMD适用于非线性非平稳分解的特点,将矢径分解为多个IMFS(Intrin-sic Mode Function),其中加入了非负判别,以保证重构矢量的相位不会发生跳变。然后,将降噪相位和分解的IMFS一一对应,重构矢量。考虑到历史继承性,该方法称为VEMD(Vector Empirical Mode Decomposition)方法。以高斯噪声污染的2个人工信号(线性调频信号、正弦+线性调频信号)和实测海杂波数据验证了本文所提出方法的性能。