触发检测算法在数字地震台的应用

介绍了在地震数据实时处理系统中常用的几种触发检测算法。以喀什地震台、巴楚地震台为例 ,对触发检测算法在国家数字地震台、区域有人值守数字地震台的实际应用进行了分析和讨论。     

云南小江断裂带北段动态触发现象研究

论文通过分析云南小江断裂北段(26°N—27.5°N,102.3°E—103.7°E)密集地震台阵(38个地震台组成)2012-2015年的地震记录,分别用基于频谱图的人工识别及小震目录的β统计两种触发判定标准研究远震是否对研究区域内小震活动存在动态触发.发现在研究时段内发生的36个7级以上远震中,7个存在着明显的触发...     

动态应力触发研究进展

本文从库仑破裂应力与动态应力触发原理、观测事实与研究现状以及存在的问题与展望等3个方面介绍了动态应力触发的研究进展。其中,在主震对余震活动、强震对后续远场地震活动、不同破裂类型的地震之间及强震对火山(泥火山)的动态应力触发作用、一次大地震中子事件之间的动态应力触发关系以及动态应力触发的时间延迟等方面进行了详细讨论。分析认为,动态应力触发理论在解释震后余震分布、远程触发以及对火山触发性喷发等方面得到了较好的结果;动态应力触发可能会受断层破裂方式和方向的影响;大地震中子事件之间的动态应力触发关系对震源研究有重要意义;动态应力触发现象普遍存在时间延迟。     

地震应急快速触发响应系统的参数配置与用户分组管理

主要介绍了中国数字地震观测网络项目应急分项软件"地震应急快速触发响应系统"中的参数配置和用户分组管理2项重要的基础功能模块,详细阐述了这2项功能的具体实现方法和原理。     

地震潮汐触发

地震潮汐触发是指由潮汐引起的应力变化而触发地震的现象,对地震潮汐触发的研究可能为断层错动引发地震的条件提供有价值的线索,一直受到国内外研究者的关注,本文对相关研究方法和研究结果进行了简要介绍和评述。在早期,地震潮汐触发研究主要是在地震活动中寻找潮汐周期。随着研究的深入,运用统计检验方法对地震活动与潮汐之间的相关性进行严格检验。时至今日,地震是否被潮汐触发的问题仍然悬而未决。不过,有研究结果表明,在强震发生前数年,震源区地震活动往往受到潮汐触发,如果这个结果被证实,将为地震预测研究提供新的线索。      

降雨触发地震研究进展

介绍了降雨触发地震研究进展,讨论了降雨触发地震研究工作中存在的不足,并提出了建议。     

CSJ延时触发数字记录地震仪

CSJ延时触发数字记录地震仪是一种便携式三路数字记录地震仪.它具有触发和定时控制两种工作方式,适合于记录区域性地震和人工地震.与之配套使用的回放仪,有串行和并行两种接口,便于联机处理.经野外实地观测,效果良好.     

地震应力触发研究

介绍地震应力触发基本理论．从地震静态和动态应力触发、粘弹性模型在地震应力触发中的应用、火山喷发或爆炸与地震触发及地震触发的其它解释等几个方面，综述近年来地震应力触发的研究进展，并对地震应力触发研究近期的发展进行展望．      

CSJ延时触发数字记录地震仪

CSJ延时触发数字记录地震仪是一种便携式三路数字记录地震仪.它具有触发和定时控制两种工作方式,适合于记录区域性地震和人工地震.与之配套使用的回放仪,有串行和并行两种接口,便于联机处理.经野外实地观测,效果良好.     

地下水触发地震的初步认识

张素欣等对地下水动态的10 a周期特征及其与强震多发期的关系所进行的研究表明,地下水10 a左右的周期结构与华北地区的强震活动有呼应关系,水位10 a周期的高值年份说明区域应力水平较高,如果某一地震构造带积累的应力水平较高,那么,水位的升降引起的应力变化有可能触发地震活动.根据大震产生的附加应力(张应力)的大小,不同应力途径的三轴压缩实验以及原地注水诱发地震的实验结果以及前人的研究成果,分析讨论了地下水触发地震的可能机制.     

调整核旋仪的一种数值方法

应用数值理论对核旋仪调整的原理进行推导,得到一种简便可行的方法。通过多次实验,结果与理论推导相符。     

国家防震减灾中心地震速报应急触发系统的设计与实现

介绍了中国地震局“九五”重点项目“地震应急快速响应信息系统”中的地震速报应急触发系统的软件设计思路、实现方法和工作流程。实现此功能是系统集成中的一项工作，通过此项功能可以将地震台网中心和地震应急指挥中心的处理系统连接起来，共同完成地震应急触发快速自动处理的任务。     

区域地震信号自动识别方法及应用(英文)

地震信号的实时、自动、准确识别对于地震自动速报和地震预警十分重要。仿真信号试验分析表明,观测数据的四阶统计量函数(BKCF)对信号与噪声在能量和(或)频率方面的微弱差异变化具有较高的分辨能力。以此为基础,本文提出了一种新的自动探测区域地震事件的方法和测定直达波震相到时的BKCF-AIC方法。为了进一步提高波震相到时测定的精度,本文首先对指定时段的P-波记录进行偏振特性分析,其次对含有P波的S波记录进行偏振滤波处理,再次应用上述方法测定震相到时。与传统算法相比,基于山东测震台网记录的区域地震震例分析结果表明,使用本文提出的方法能够大幅度降低地震事件误检、漏检率,进一步提高了震相识别精度。     

近震信号检测参数设置研究

地震信号检测是进行各种地震数据分析和处理的首要任务,STA/LTA方法具有算法简单、便于实时处理等特点,被广泛应用于地震信号检测.结合实际震例数据研究STA/LTA方法进行地震信号检测的各种影响因素,得到该方法进行检测时最合理的参数设置范围.     

A trigger mechanism for the Lake Nyos disaster

The catastrophic release of carbon dioxide gas from Lake Nyos on 21 August 1986 is discussed in the context of the buoyancy reversal instability. Originally proposed by Randall (1980) [Randall, D.S., 1980. Conditional instability of the first kind upside-down. Journal of Atmospheric Sciences 37: 125–130.] and Deardoff (1980) [Deardoff, J.W., 1980. Cloud-top entrainment instability. Journal of Atmospheric Sciences 37: 131–147.] for the `cloud-top entrainment instability' of stratocumulus clouds, the buoyancy reversal instability has been studied experimentally in water tank experiments by Shy and Breidenthal (1990) [Shy, S.S., Breidenthal, R.E., 1990. Laboratory experiments on the cloud-top entrainment instability. Journal of Fluid Mechanics 214: 1–15.], who identified three criteria for instability. The initial disturbance must be sufficiently large, so that its Reynolds number is above the mixing transition, its Richardson number must be less than one to achieve overturning and mixing, and the buoyancy reversal parameter must be greater than a critical value, of order one. The implications and applicability of these criteria to Lake Nyos are discussed. The criterion for the Reynolds number is easily satisfied for typical wind velocities in the Lake Nyos region. Similarly, the Richardson number based on incident turbulence is easily less than unity, and therefore satisfy the second criterion for instability. In the case of Lake Nyos, the continuous release of carbon dioxide at the bottom of the lake increases the value of the buoyancy reversal parameter until it reaches its critical value, at which point an explosion occurs. This instability provides a plausible trigger for the 1986 explosion. After each explosion, the buoyancy reversal parameter returns to below its critical value, only to slowly rise again over time, as CO₂ continues to enter the lake, setting the stage for the next explosion. Future explosions may be avoided if the value of the buoyancy reversal parameter is prevented from approaching its critical value by artificial mixing at the thermocline, such as with a bubble plume.     

A neural network approach for the real-time detection of faults

Fault detection is an essential part of the operation of any chemical plant. Early detection of faults is important in chemical industry since a lot of damage and loss can result before a fault present in the system is detected. Even though fault detection algorithms are designed and implemented for quickly detecting incidents, most these algorithms do not have an optimal property in terms of detection delay with respect to false alarm rate. Based on the optimization property of cumulative sum (CUSUM), a real-time system for detecting changes in dynamic systems is designed in this paper. This work is motivated by combining two fault detection (FD) strategies; a simplified procedure of the incident detection problem is formulated by using both the artificial neural networks (ANN) and the CUSUM statistical test (Page–Hinkley test). The design of a model-based residual generator is intended to reveal any drift from the normal behavior of the process. In order to obtain a reliable model for the normal process dynamics, the neural black-box modeling by means of a nonlinear auto-regressive with eXogenous input (NARX) model has been chosen in this study. This paper also shows the choice and the performance of the neural network in the training and test phases. After describing the system architecture and the proposed methodology of the fault detection, we present a realistic application in order to show the technique’s potential. The purpose is to develop and test the fault detection method on a real incident data, to detect the change presence, and pinpoint the moment it occurred. The experimental results demonstrate the robustness of the FD method.     

光滑地表面毁伤检测方法研究

光滑地面毁伤程度评估非常重要,目前评估方法主要是基于光学图像,可是在恶劣的气候或环境条件下,很难获得光学图像,合成孔径雷达（SAR）克服了这个缺点. SAR图像是地表结构和电特征等地球物理参数的映射,通过SAR图像反演地表结构参数,可以推测出光滑地面毁伤程度. 本文以几何光学模型（GOM）为基础,建立神经网络反演模型,以获得光滑地表面受损后的粗糙度参数：表面均方根高度（σ）和表面相关长度（l）,并进一步评估光滑地表面受损程度. 实验结果表明该方法可行.     

A new approach for separating mixed model parameters:application to simultaneous inversion of earthquake source parameters

A method for simultaneous determination of mixed model parameters,which have different physical dimensions or different responses to data,is presented.Mixed parameter estimation from observed data within a single model space shows instabilities and trade-offs of the solutions. We separate the model space into N-subspaces based on their physical properties or computational convenience and solve the N-subspaces systems by damped least-squares and singular-value decomposition. Since the condition number of each subsystem is smaller than that of the single global system,the approach can greatly increase the stability of the inversion. We also introduce different damping factors into the subsystems to reduce the tradeoffs between the different parameters. The damping factors depend on the conditioning of the subsystems and may be adequately chosen in a range from 0.1 % to 10 % of the largest singular value. We illustrate the method with an example of simultaneous determination of source history,source geometry,and hypocentral location from regional seismograms,although it is applicable to any geophysical inversion.     

A Bayesian probabilistic approach for structure damage detection

A Bayesian probabilistic approach is presented for the damage detection of multistorey frame structures. In this paper, a Bayesian probabilistic approach is applied to identify multiple damage locations using estimated modal parameters when (1) the measurement data are potentially corrupted with noise, (2) only a small number of degrees of freedom are measured, and (3) a few fundamental modes are estimated. To reduce the potentially intensive computational cost of the proposed method, a branch-and-bound search scheme is proposed and a simplified approach for the modelling of multistorey frame structures is employed. A six-storey shear frame example and two multistorey frame examples, with multiple damage locations, are presented to illustrate the applicability of the proposed approach. © 1997 John Wiley & Sons, Ltd.     

A tool for the ages: The Probabilistic Cosmogenic Age Analysis Tool (P-CAAT)

While revolutionary to the geomorphic community, the application of terrestrial cosmogenic nuclide (TCN) dating is complicated by geological uncertainties, which often lead to skewed or poorly clustered TCN age distributions. Although a range of statistical approaches are typically used to detect and remove outliers, few are optimized for analysis of TCN datasets. Many are mean- or median-based and therefore explicitly assume a single probability distribution (e.g., Mean Squared Weighted Deviates, Chauvenet's Criterion, etc.). Given the ubiquity of pre- and post-depositional modification of rock surfaces, which occur at different rates in different geomorphic settings, these approaches struggle with multimodal distributions which often characterize TCN datasets. In addition, most statistical approaches do not propagate measurement or production rate uncertainties, which become increasingly important as dataset size or clustering increases. Finally, most approaches provide arithmetic single solutions, irrespective of geologic context.To address these limitations, we present the Probabilistic Cosmogenic Age Analysis Tool (P-CAAT), a new approach for outlier detection and landform age analysis. This tool incorporates both sample age and geologic uncertainties and uses Monte Carlo simulations to eliminate dataset skewness by isolating component normal distributions from a cumulative probability density estimate for datasets with three or more samples. This approach allows geologic context to inform post-analysis interpretations, as researchers can assign landform ages based upon statistically distinct subpopulations, informed by the characteristics of geomorphic systems (e.g., exhumation of boulders as moraines degrade through time). To evaluate the effectiveness of P-CAAT, we analyzed a range of synthetic TCN datasets and compared the results to commonly used statistical approaches for outlier detection. Irrespective of dataset size or clustering, P-CAAT outperformed other approaches and returned accurate solutions that improve in precision as sample size increases. To enable more comprehensive utilization of our approach, P-CAAT is packaged with a GUI interface and is available for download at kgs. uky.edu/anorthite/PCAAT.