地震数据采集器中△-∑AD转换器512 kHz数据流的仿真

根据Δ-∑AD转换器原理,通过编程将给定的输入信号转换为1位串行Δ-∑数据流。用此数据流可以仿真地震数据采集器中的滤波抽样过程,检验设计构造的各级滤波参数能否满足地震观测的需要。为了证明该仿真程序的正确性,本文介绍了利用CS5376A公布的数字滤波参数对数据流进行滤波验证。     

△-∑A/D转换技术及在地震勘探中的应用

△调制型A／D转换技术是△-∑A／D转换技术的基础．本文阐述了△调制型A／D转换器的基本原理。对信噪比和△-∑A／D转换器的噪声成形作用进行了分析与推导,深入探讨了△-∑A／D阶次、信噪比及采样率之间的关系,并由此得出结论：当代遥测地震仪采用24位四阶△-∑A／D转换器是高分辨率地震勘探精度的基本要求(瞬时动态范围或信噪比为120 dB)．     

EDAS-C24型数字测震仪实时数据的解码及加速度和位移仿真的实现

本文尝试使用了一种图形编程语言进行数据解码和仿真研究,阐述了用该语言实现EDAS-C24型数字测震仪实时数据流的解码过程,提出了在G语言下利用数字滤波器逼近模拟积分器及模拟微分器响应实现对解码数据实时仿真的方法,并通过设定频带宽度,比较了设计的补偿滤波响应和实际的幅频响应的一致性.结果表明,在设定的频带内,补偿滤波响应和实际的幅频响应是一致的,仿真的精度是理想的,成果已经在广东省地震科普馆的地震互动区部署运行,取得了一定的实效.     

ZD8数字地电仪的特点

ZDSB数字地电仪用8031单片机作为中心控制单元，ICL7650、AD7710分别构成主放大器和A／D转换器。因ICL7650具有崭波稳零和高输入阻抗的性质，AD7710内部∑-△调制器和可编程数字滤波器可获得自动调零和较高的工频共模、串模抑制比及24位的高分辨率，另外，ZDSB数字地电仪还配备了功能完善的运行软件从而获得了较高的性能。     

武定6.5级地震序列的地震应力降研究

以Brune提出的中小地震圆盘形破裂位错模式为理论基础，研究了地面运动峰值参数（r.d)和（r.v)对地震应力降△σ的依赖性，并考虑地球介质Q值对峰值参数的影响，利用武定M6．5级地震序列的近场数字记录地震资料，由此导出了用峰值位移d和峰值程度v求地震应力降△σ的关系式：lg(g.d/e^-qr)=-10.56 2/3lgM0 1/3lg△σ；lg（r，v/e^-qr)=-2.566 1/3lgM0 2/3lg△σ.用上述公式测定了武定地震序列的地震应力降△σ，结果给出地震序列的应力降△σ构大多数在5．0－50MPa的范围内，是典型的高应力降序列。通过分析应力降的时空分布特征，发现应力参数与余震活动的频度及强度相关，也与地震构造背景相关。研究结果还表明用地面运动峰值参数估算地震应力降是一种新的实用性较强的方法。     

鲁15井水位与塌陷地震关系的研究

介绍了鲁１５井及附近的矿井塌陷地震概况，利用鲁１５井水位对矿井塌陷地震响应的观测资料，分析了鲁１５井水位的塌陷地震前兆．指出大塌陷前的∑△Ｈ－ｔ和Ｎｏ－△ｔ曲线都有异常变化，而且这一变化出现在大塌陷前一个月左右，因此有可能利用鲁１５井的塌陷地震前兆对较大塌陷做出预测。     

1999年9月21日台湾省集集强余震序列发生时间的规律性

使用1999年9月20日至11月1日的CDSN宽频带（BPZ）地震记录,对台湾省集集地震的强震震级、震源性质、震源物理参数和发生时间进行研究。主要结果:①确定集集地震是强震群类型的地震活动,主震[m(T)8.51,MW7.3]位于中央山脉上,横切中央山脉的北西向北斗-玉里断裂,是主要地震活动构造;②集集强震序列的平均应力降△σ为4.272×103kPa,平均视应力ησ为2.136×103kPa,它们是地震断层面上随着震源尺度等变化而变化的物理量;③决定地震效率η的震源释放能量-△E和传播地震波能量Es,分别从BPZ地震波5个倍频程的滤波数据和假设视应力等于二分之一应力降的条件下求取;④强余震的发震时间对数lg△t（时间单位为s）,与一些震源物理参数有显著的负相关性,证实了能量积累多、应力积聚高的地方率先发震。并且第一次强震以后,强余震发生时间和强度之间保持显著的衰减关系。这些关系式,如△t=1015.54-1.48m（r）和△t=1017.55-2.00MW等,对早期识别出如同集集强震群类型的地震活动时,预测强余震时间和强度有实际应用意义。     

煤矿塌方地震资料的初步分析

本文对矿区塌方地质构造的分析表明,矿井塌方地震与矿区的局部地质构造有密切的关系。通过对山东陶压煤矿塌方地震资料的初步分析表明,在较大的塌方地震发生之前,有以下异常出现:小塌方地震次数增多,∑N——t曲线、∑E~(1/2)—t曲线、∑L—t曲线及N_o—∑△t曲线急剧变化。这些异常变化一般出现在较大塌方地震前12——70天。依此有可能对较大塌方地震做出预报。     

位移和加速度融合的自适应多速率Kalman滤波方法

多速率Kalman滤波方法可用于低采样率的位移和高采样率的加速度数据融合,而未知的噪声协方差信息则显著制约着多速率Kalman滤波精度.本文通过将多速率Kalman滤波转换为传统的单速率Kalman滤波,建立了Kalman滤波增益的自协方差矢量与未知的加速度谱密度和观测噪声参数间的线性函数模型,并采用最小二乘估计方法对未知的噪声协方差参数进行估计,进而有效地提高了多速率Kalman滤波精度.数值仿真和震动台实验结果验证了本文方法的正确性和有效性.     

地震数据采集器后级滤波器的设计

以ADS1281为例,介绍新一代地震数据采集器后级滤波器设计。该后级滤波器包括变抽样率的梳状滤波器、有限脉冲响应(FIR1)4抽1滤波器和有限脉冲响应(FIR2)2抽1滤波器。其中,FIR1 4抽1滤波器和FIR2 2抽1又分为最小相位、线性相位和瞬态3种滤波器,文中使用设计的最小相位滤波抽取器对仿真的正弦波进行滤波验证,结果表明,通带波动和阻带衰减满足中国数字测震台网技术规程的要求。     

Comparison of deterministic ensemble Kalman filters for assimilating hydrogeological data

Groundwater models are critical decision support tools for water resources management and environmental remediation. However, limitations in site characterization data and conceptual models can adversely affect the reliability of groundwater models. Therefore, there is a strong need for continuous model uncertainty reduction. Ensemble filters have recently emerged as promising high-dimensional data assimilation techniques. Two general categories of ensemble filters exist in the literature: perturbation-based and deterministic. Deterministic ensemble filters have been extensively studied for their better performance and robustness in assimilating oceanographic and atmospheric data. In hydrogeology, while a number of previous studies demonstrated the usefulness of the perturbation-based ensemble Kalman filter (EnKF) for joint parameter and state estimation, there have been few systematic studies investigating the performance of deterministic ensemble filters. This paper presents a comparative study of four commonly used deterministic ensemble filters for sequentially estimating the hydraulic conductivity parameter in low- and moderately high-dimensional groundwater models. The performance of the filters is assessed on the basis of twin experiments in which the true hydraulic conductivity field is assumed known. The test results indicate that the deterministic ensemble Kalman filter (DEnKF) is the most robust filter and achieves the best performance at relatively small ensemble sizes. Deterministic ensemble filters often make use of covariance inflation and localization to stabilize filter performance. Sensitivity studies demonstrate the effects of covariance inflation, localization, observation density, and conditioning on filter performance.     

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.     

A stream tracer technique employing ionic tracers and specific conductance data applied to the Maimai catchment,New Zealand

The stream tracer technique and transient storage models (TSMs) have become common tools in stream solute and hyporheic exchange studies. The expense and logistics associated with water sample collection and analysis often results in limited temporal resolution of stream tracer breakthrough curves (BTCs). Samples are often collected without a priori or real‐time knowledge of BTC information, which can result in poor sample coverage of the critical shoulder (initial rise) and tail (post‐steady state fall) of the BTC. We illustrate the use of specific conductance (SC) measurements as a surrogate for conservative dissolved tracer (Br⁻) samples. The advantages of collecting SC data for use in the TSM are (1) cost, (2) ease of data collection, and (3) well‐defined breakthrough curves, which strengthen TSM parameter optimization. This method is based on developing an ion concentration (IC)–SC relationship from limited discrete tracer solute samples. SC data can be collected on a more frequent basis at no additional analysis cost. TSM simulations can then be run for the conservative tracer data derived from SC breakthrough curves and the IC–SC relationship. This technique was tested in a 120 m reach of stream (2–60 m subreaches) in the Maimai M15 catchment, New Zealand during baseflow recession. Dissolved LiBr was injected for 12·92 h, with Br⁻ as the conservative ion of interest. Four TSM simulations using the OTIS model are optimized using UCODE to fit (1) Br⁻ data derived from the Br⁻–SC relationship (n = 1307 observations at each of two stream sampling sites), (2) all stream Br⁻ data collected (n = 58 in upper reach, n = 60 in lower reach), (3) half of the stream Br⁻ data collected, and (4) 20 stream Br⁻ samples from each site. No two simulations resulted in the same optimal parameter values. Results suggest that the greater the frequency of observations, the greater the confidence in estimated parameter values. Br⁻–SC simulations resulted in the best overall model fits to the data, with the lowest calculated error variance of 6·37, narrowest 95% parameter estimate confidence intervals, and the highest correlation coefficient of 0·99 942, among the four simulations. This is largely due to the improved representation of the shoulder and tail of the BTC with this method. The IC–SC correlation method is robust in situations in which (1) changes in background SC data can be accounted for, and (2) the data used to define the IC–SC relationship are representative of the range of data collected. This method provides more efficient sample analysis, improved data resolution, and improved model results compared to the alternative stream tracer data gathering methods presented. Additionally, we describe a new parameterization of the cross‐sectional area of the stream during flow recession, as a function of discharge, based on a stream hydraulic geometry relationship. This variant of the OTIS model provides a more realistic representation of stream dynamics during unsteady discharge. Copyright © 2005 John Wiley & Sons, Ltd.     

位场异常分离的递减半径迭代法

本文提出了位场区域-剩余异常分离的空间域递减半径迭代法.由给定半径的圆周上八点位场值的算术平均导出一个新的八点圆周平均公式,它是一个由重磁数据计算区域异常的滤波器.该滤波器的传递函数有一主瓣和多个旁瓣,且半径越大,旁瓣越多,滤波器特性越差.由从大到小不同半径对应的传递函数的连乘积构造了递减半径迭代传递函数,它以大半径为参变量.递减半径迭代传递函数类似低通滤波器,其截止波数与大半径成反比.由递减半径迭代传递函数,给出空间域分离区域异常的递减半径线性迭代法,由重磁数据减去区域异常求得剩余异常.进一步,通过构造非线性修正系数,把空间域递减半径线性迭代法中线性迭代公式变成非线性迭代公式,得到空间域递减半径非线性迭代法.重磁理论模型及安徽泥河铁矿重磁资料的试验表明,空间域递减半径非线性迭代法可有效地压制假异常和高频干扰以及减少异常畸变,并能有效地分离出区域异常和剩余异常.     

一种基于频率域偏振分析提高三分量地震资料信噪比的方法

三分量地震资料包含着丰富的运动学和动力学信息,各种随机噪声的存在严重降低了资料的信噪比,给有效信息的提取带来了一定的困难.本文在引入多窗谱分析方法的基础上,通过对谱密度矩阵特征问题的求解提取三分量地震记录的偏振参数,实现频率域偏振分析;根据所求得的偏振参数以及随机噪声和有效信号的偏振特性差异,设计相应的自适应滤波器,通过该滤波器的滤波作用,最终实现压制随机噪声的目的.     

Parameter estimation in ensemble based snow data assimilation: A synthetic study

Estimating erroneous parameters in ensemble based snow data assimilation system has been given little attention in the literature. Little is known about the related methods’ effectiveness, performance, and sensitivity to other error sources such as model structural error. This research tackles these questions by running synthetic one-dimensional snow data assimilation with the ensemble Kalman filter (EnKF), in which both state and parameter are simultaneously updated. The first part of the paper investigates the effectiveness of this parameter estimation approach in a perfect-model-structure scenario, and the second part focuses on its dependence on model structure error. The results from first part research demonstrate the advantages of this parameter estimation approach in reducing the systematic error of snow water equivalent (SWE) estimates, and retrieving the correct parameter value. The second part results indicate that, at least in our experiment, there is an evident dependence of parameter search convergence on model structural error. In the imperfect-model-structure run, the parameter search diverges, although it can simulate the state variable well. This result suggest that, good data assimilation performance in estimating state variables is not a sufficient indicator of reliable parameter retrieval in the presence of model structural error. The generality of this conclusion needs to be tested by data assimilation experiments with more complex structural error configurations.     

Dual state-parameter estimation of root zone soil moisture by optimal parameter estimation and extended Kalman filter data assimilation

With well-determined hydraulic parameters in a hydrologic model, a traditional data assimilation method (such as the Kalman filter and its extensions) can be used to retrieve root zone soil moisture under uncertain initial state variables (e.g., initial soil moisture content) and good simulated results can be achieved. However, when the key soil hydraulic parameters are incorrect, the error is non-Gaussian, as the Kalman filter will produce a persistent bias in its predictions. In this paper, we propose a method coupling optimal parameters and extended Kalman filter data assimilation (OP-EKF) by combining optimal parameter estimation, the extended Kalman filter (EKF) assimilation method, a particle swarm optimization (PSO) algorithm, and Richards’ equation. We examine the accuracy of estimating root zone soil moisture through the optimal parameters and extended Kalman filter data assimilation method by using observed in situ data at the Meiling experimental station, China. Results indicate that merely using EKF for assimilating surface soil moisture content to obtain soil moisture content in the root zone will produce a persistent bias between simulated and observed values. Using the OP-EKF assimilation method, estimates were clearly improved. If the soil profile is heterogeneous, soil moisture retrieval is accurate in the 0-50 cm soil profile and is inaccurate at 100 cm depth. Results indicate that the method is useful for retrieving root zone soil moisture over large areas and long timescales even when available soil moisture data are limited to the surface layer, and soil moisture content are uncertain and soil hydraulic parameters are incorrect.     

用于地震观测的瞬态滤波试验数据分析

地震数据采集器中的滤波技术是影响地震观测数据质量的重要因素。本研究通过实测数据对比分析了最小相位滤波、线性相位滤波和瞬态滤波对观测数据的影响程度。实测波形数据证实了理论分析的预期,最小相位滤波在观测地方性微小地震时,初动半周期及后续波的失真均较大,利用波形作深入研究时,应注意该失真的影响;线性相位滤波引起的"前缀"可能会干扰震相的正确判读,不宜用于以震相分析为主要用途的地方震观测;瞬态滤波兼有前两类滤波的优点而无其缺点,是观测地方震和水库地震的优良滤波技术,但应用瞬态滤波必须提高采样率。