消除强震加速度记录数字化误差的方法和处理软件

本文详细地分析了用数字化仪和激光扫描仪对模拟加速度记录进行数字化时所产生的误差及消除这些误差的方法，并开发了相关处理软件。数字化误差由数字化设备的系统误差和读数员在操作过程中的随机误差迭加而成，随机数字化误差是具有各态历经性质的、其振幅按高斯规律分布的平稳随机过程。利用激光扫描仪做强震记录数字化，工作效率很高。本文给出了激光扫描仪分析处理软件和消除数字化噪声实例。     

电磁法数据处理的奇异值分解法

本文提出用奇异值分解方法处理电磁响应数据.根据电磁响应数据的奇异值分布特征,可以指出有用信号和随机误差所对应的奇异值范围.截断随机误差所对应的奇异值,利用与有用信号对应的特征象重构数据,可以消除随机误差.对加入随机噪声的理论数据处理的结果表明,这种方法的效果明显,随机噪声的标准差可降低60％多.另外,利用不同区段的特征象重构数据,可区分不同级次的电磁响应特征.最后,给出对实测数据处理的结果.     

消除探地雷达数据的子波衰减和频散的反滤波方法

消除探地雷达数据的子波衰减和频散可以很好地提高探地雷达的勘探深度和勘探分辨率.常用的消除探地雷达数据的子波衰减和频散方法为反Q滤波方法.该方法需要利用地下介质的Q参数,但是正确求取地下介质的Q参数很困难.针对这一问题,本文提出了一种消除探地雷达数据的子波衰减和频散的反滤波方法.该方法以地下介质反射系数是随机数为前提,利用地下介质等效滤波器具有最小相位这个特性,通过求取等效滤波器的振幅谱来求取等效滤波器的反滤波器.最后,利用该反滤波器对探地雷达数据进行反滤波,实现消除探地雷达数据的子波衰减和频散.     

探地雷达衰减补偿逆时偏移成像方法

探地雷达信号在地下介质中传播时易受到电导率所产生的衰减影响,从而使得传统偏移成像结果在高衰减区域变得模糊.本文提出了衰减补偿的逆时偏移方法来消除电导率的影响.该方法基于麦克斯韦方程组实现电磁波的正演模拟和逆时传播.通过改变衰减项的正负号,保证了逆时传播的时间对称性,从而能够重构出原始波场,实现衰减补偿.数值实验比较了传统逆时偏移方法和衰减补偿逆时偏移方法在存在高导异常区域情况下的成像效果,结果证明了衰减补偿逆时偏移方法能够很好地恢复由电导率造成的信号衰减,从而提高探地雷达剖面的分辨率.     

用随机方法模拟唐山7.1级余震地震动场

在系统介绍用随机方法模拟地震动的基础上,用该方法模拟了唐山7.1级余震地震动场。模拟结果表明,唐山地区发生MS7.1级余震时,该地区产生了强烈的地震动,很多区域加速度峰值超过400cm/s2,地震断层面长65km,宽13.5km,地震过程中断层面的平均滑动为1.08m。模拟与记录的地震动持时符合得不好,其原因是随机方法中的经验关系大都是在美国大陆得到的,所以建议加强中国大陆相应的地震动经验关系的研究,使随机方法能更好地适用于中国大陆。尽管如此,由于用随机方法模拟的地震动峰值和反应谱与记录符合得比较好,这些模拟结果可以作为建筑物抗震设防的地震动输入。     

基于等效群速度的非平稳地震动拟合方法研究

基于地震动能量传播速度为群速度这一概念,回顾了相位微分和窄带滤波两种频率相依波包时延计算方法及其在非平稳地震动相位拟合中的应用,归纳给出了一种非平稳地震动生成方法,通过模拟2条典型的海底与陆地地震动验证了方法的有效性,并将该方法应用于区域非平稳地震动场模拟中。结果表明:利用该方法所得模拟地震动记录平均加速度反应谱与原记录加速度反应谱有较高的一致性,而且能很好地再现地震的非平稳特性。     

自适应噪声消除器在地电场观测数据处理中的应用

在地电场和电阻率同场地观测的台站, 地电场观测必然会受到地电阻率观测人工供电的干扰, 尤其是当地电场观测的采样率提高到1次/s以上时, 这种干扰更是无可避免, 而且不易消除。 该文阐述了应用自适应噪声消除器对受种干扰的地电场观测数据进行处理, 消除观测数据中的干扰噪声, 从而获得地电场真实信号波形。 对实际观测数据的处理结果表明, 采用此方法可以很好的消除秒采样地电场观测数据中地电阻率供电产生的干扰。 这种方法还可用于消除其他观测方法中存在的有规律的干扰。     

沉陷区域埋地管线数值模拟分析

场地的不均匀沉陷是导致埋地管线破坏的重要原因之一。本文考虑了材料非线性、几何非线性以及管土接触非线性,将管线计算分析模型模拟为四节点薄壳单元结构,周围填覆土体采用八节点六面体单元划分。管土相互作用模拟为三维刚性与柔性的面面接触单元结构,并采用线性位移加载来模拟土体的沉陷作用,对三维薄壳有限元模型进行数值计算分析。通过比较不同参数,如沉陷长度、沉陷深度、埋深、管径、径厚比、土特性等对管线的反应影响,得出管线在沉陷情况下的应力和应变的关系,通过算例分析,说明了该方法能更好地模拟管线的破坏过程,该方法将为沉陷区域埋地管线数值模拟提供理论分析依据。     

卢龙地震动场的预测

分别用经验格林函数方法和随机方法对卢龙ML5.7地震的地震动进行模拟对比研究,结果显示:用经验格林函数方法模拟得到的波形和反应谱都与原始记录接近,用该方法模拟的地震动,无需掌握场地的具体情况;对于无小震记录的地区,如果知道了其场地情况与附近有小震记录地区相似,可以用该小震记录作为经验格林函数模拟地震动。对于不能用经验格林函数方法模拟地震动的地区,可以用随机方法模拟地震动。用随机方法模拟地震动具有简单、方便、无需小震记录的优点。根据卢龙场地具体条件,尝试用两种方法结合预测了卢龙地震加速度场,结果比较好地反映了断层周围加速度的峰值分布规律。     

俯冲带浅壳和上地幔地震竖向位移谱阻尼修正系数模型

基于日本K-NET和KiK-net强震台网获取的7635条浅壳和上地幔地震记录的统计分析,考虑阻尼比,谱周期点及场地类别的影响,采用最小二乘法建立竖向位移谱阻尼修正系数模型,并通过随机效应模型分离出模型残差及其标准差,探究各参数对模型随机误差的影响。研究表明:采用一个简单的阻尼比对数的二次式能很好的模拟阻尼比的影响;模型事件间残差与震级显著相关,事件内残差与震源距离的相关性较大;在周期0.6 s前,震源效应引起的随机误差小于其他效应引起的随机误差,但0.6 s后,场地效应引起的随机误差较其他效应引起的随机误差小;在整个周期上,路径效应与其他效应引起的随机误差占比大。文中的研究结果可直接用于调整不考虑震源及震源距的设计反应谱。     

ADAPTIVE SIGNAL PROCESSING THROUGH STOCHASTIC APPROXIMATION*

One of the problems in signal processing is estimating the impulse response function of an unknown system. The well-known Wiener filter theory has been a powerful method in attacking this problem. In comparison, the use of stochastic approximation method as an adaptive signal processor is relatively new. This adaptive scheme can often be described by a recursive equation in which the estimated impulse response parameters are adjusted according to the gradient of a predetermined error function. This paper illustrates by means of simple examples the application of stochastic approximation method as a single-channel adaptive processor. Under some conditions the expected value of its weight sequence converges to the corresponding Wiener optimum filter when the least-mean-square error criterion is used.     

Real-time flood forecasting with the use of inadequate data

Abstract

A modelling scheme is developed for real-time flood forecasting. It is composed of (a) a rainfall forecasting model, (b) a conceptual rainfall-runoff model, and (c) a stochastic error model of the ARMA family for forecast error correction. Initialization of the rainfall-runoff model is based on running this model on a daily basis for a certain period prior to the flood onset while parameters of the error model are updated through the Recursive Least Squares algorithm. The scheme is suitable for the early stages of operation of flood forecasting systems in the presence of inadequate historical data. A validation framework is set up which simulates real-time flood forecasting conditions. Thus, the effects of the procedures for rainfall-runoff model initialization, forecast error correction and rainfall forecasting are assessed. Two well-known conceptual rainfall-runoff models (the Soil Moisture Accounting model of the US National Weather Service River Forecast Service—SMA-NWSRFS and TANK) together with data from a Greek basin are used for illustration purposes.     

Stochastic observation error and uncertainty in water quality evaluation

When evaluating water quality, the influence of physical weight of the observed index is normally taken into account, but the influence of stochastic observation error (SOE) is not adequately considered. Using Monte Carlo simulation, combined with Shannon entropy, the Principle of Maximum Entropy (POME) and Tsallis entropy, this study investigates the influence of stochastic observation error (SOE) for two cases of the observed index: small observation error and large observation error. Randomness and fuzziness represent two types of uncertainties that are deemed significant and should be considered simultaneously when developing or evaluating water quality models. To that end, three models are employed here: two of the models, named as model I and model II, consider both the fuzziness and randomness, and another model, considers only fuzziness. The results from three representative lakes in China show that for all three models, the influence of stochastic observation error (SOE) on water quality evaluation can be significant irrespective of whether the water quality index has a small observation error or a large observation error. Furthermore, when there is a significant difference in the accuracy of observations, the influence of stochastic observation error (SOE) on water quality evaluation increases. The water quality index whose SOE is minimum determines the results of evaluation.     

Using stochastic state‐space modelling to specify and reduce hydrograph error

A Bayesian post‐processor is used to generate a representation of the likely hydrograph forecast flow error distribution using raingauge and radar input to a stochastic catchment model and its deterministic equivalent. A hydrograph ensemble is so constructed. Experiments are analysed using the model applied to the River Croal in north‐west England. It is found that for rainfall input to the model having errors less than 3mm h^?1, corresponding to about a 15% error in peak flow, the stochastic model outperforms the deterministic model. The range of hydrographs associated with the different model simulations and the measured hydrographs are compared. The significant improvement possible using a stochastic approach is demonstrated for a specific case study, although the mean hydrograph derived using the stochastic model has an error range associated with it. Copyright © 2007 John Wiley & Sons, Ltd.     

一种改进的近断层脉冲型地震动模拟方法

本文基于小波包技术的随机地震动模拟方法,提出一种改进的参数化随机近断层脉冲型地震动模拟方法。然后,通过识别和提取近断层脉冲型地震动数据库中脉冲型地震动的特征参数,建立了基于震源、传播路径和场地特征等参数的脉冲模型参数预测方程。最后,通过模拟实际记录和误差分析检验了改进的模拟方法的有效性。结果表明:应用改进的模拟方法得到的地震动时程无论在波形、频率特性还是峰值上均与实际记录具有较好的一致性。改进的模拟方法在保留地震动时频非平稳性的基础上,能够有效地提高近断层脉冲型地震动的模拟效果,并且能够很好地体现脉冲型地震动的主要特征。     

川滇地区应变率场分布及其变化特征研究

基于GPS多期复测资料, 利用最小二乘配置方法计算川滇地区应变参数, 分析该区域应变率场分布及其变化特征并探讨其分布与强震关系。 研究结果表明: ① 各时段应变率场空间分布的明显变化应属于大于GPS资料误差的真实地壳构造形变信息; ② 最大剪应变率及第一、 第二剪应变率的结果反映了走滑断裂对区域变形的显著控制; ③ 主应变率, 东西、 南北向应变率场动态结果反映的汶川地震孕震的空间尺度较大; ④ 在本区大致反映北东向与北西向剪切变形的第一剪应变率、 东西向应变率、 南北向应变率及最大剪应变率与6级以上地震对应较好。     

Calibration of the specific barrier model to Iranian plateau earthquakes and development of physically based attenuation relationships for Iran

Earthquake ground-motion relationships for soil and rock sites in Iran have been developed based on the specific barrier model (SBM) used within the context of the stochastic modeling and calibrated against up-to-date Iranian strong-motion data. A total of 171 strong-motion accelerograms recorded at distances of up to 200 km from 24 earthquakes with moment magnitudes ranging from Mw 5.2 to 7.4 are used to determine the region-specific source parameters of this model. Regression analysis was conducted using the “random effects” methodology that considers both earthquake-to-earthquake (inter-event) variability and within-earthquake (intra-event) variability to effectively handle the problem of weighting observations from different earthquakes. The minimization of the error function in each iteration of the “random effects” procedure was performed using the genetic algorithm method. The residuals are examined against available Iranian strong-motion data to confirm that the model predictions are unbiased and that there are no significant residual trends with distance and magnitude. No evidence of self-similarity breakdown is observed between the source radius and its seismic moment. To verify the robustness of the results, tests were performed to confirm that the results are unchanged if the number of observations is changed by removing different randomly selected datasets from the original database. Stochastic simulations, using the derived SBM, are then performed to predict peak ground-motion and response spectra parameters for a wide range of magnitudes and distances. The stochastic SBM predictions agree well with the new empirical regression equations proposed for Iran, Europe and Middle East in the magnitude–distance ranges well represented by the data. It has been shown that the SBM of this study provides unbiased ground-motion estimates over the entire frequency range of most engineering interests (1–10 Hz) for the Iranian earthquakes. Our results are also important for the assessment of hazards in other seismically active environments in the Middle East and Mediterranean regions.     

ADVANCED METHOD FOR SELF-ADAPTIVE ESTIMATION OF RESIDUAL STATIC CORRECTIONS*

The estimation of residual static corrections is investigated as a linear system. For 1200% coverage shot one way offset weighting functions—or in other words, estimation error operators—are computed. Assuming zero time shift determination errors and zero RNMO it is seen that large residual corrections will distort the effectivity of the estimation. With an iterative procedure which includes the repeated averaging according to depth point, shot point, and geophone point the effectivity of the method becomes more favourable. This can be learnt from the evaluation of estimation error operators computed by recursive formulae. In practice, due to the time shift determination errors, the routine does not give improved results in the desired level. Errors can be reduced with a more reliable time shift determination routine. For detecting and suppressing the unfavourable effect of time shift errors still remaining in the data a self-adaptive method was developed. In this non linear routine the data are evaluated at all three averaging processes according to limit values and weighting factors computed from the data itself. Field examples processed in different ways are presented.     

地震波时变修正Kanai-Tajimi非平稳随机模型的建立

利用谐小波变换对实际强震记录的时变谱进行估计,并统计分析了远场3类不同场地上地震波的时变谱特征,分析发现对于硬场地上的远场地震波在时域内平稳段较短,下降段衰减较快,而在频域内则具有较大的中心频率和较宽的频带.利用均匀调制非平稳模型和时变修正Kanai-Tajimi非平稳模型模拟地震波的时变谱,把非线性函数的参数识别问题转化成求解无约束优化问题,利用拟牛顿迭代法求得最优解,得到3类不同场地上这两种模型的参数具体取值以及参数函数集的具体表达式.为了定量地确定模拟模型的精度,定义了误差函数,验证了所提时变谱参数识别方法的精度,给出了与建筑抗震规范相对应的不同场地不同烈度下多遇和罕遇地震的谱强度因子的大小.最后提出了利用求解时变线性微分方程组来合成非平稳地震波的方法.