Quantification and interpretation of seismicity

Methods based on acoustic emission and microseismicity (AE/MS) have proven to be valuable for monitoring microcracking at the Underground Research Laboratory (URL) in Canada. The source locations of the seismic events induced by the excavation have helped to map out the extent of the excavation damage/disturbed zone (EDZ) around tunnels. This paper describes methods for advanced processing and interpretation of AE/MS data, and the quantification of changes in material properties using velocity interferometry. Examples of methods that are generally not used routinely in the analysis of AE/MS data are given. These include (1) long-term spatial and temporal source parameter trends and magnitude–frequency studies; (2) source mechanism analysis; and (3) source location refinement by the use of relative location, and clustering techniques. Results from these studies are shown to aid in the understanding of the effect of confining pressure on AE/MS activity around tunnels, and the mechanics of rock failure in the EDZ. Also, the reduction of source location error is shown to be critical for delineating structures that may exist in clusters of AE/MS data. Finally, examples of the use of seismic sources to produce repeat measurements of seismic velocity along raypaths in 3D orientations through a rock mass are given. This is found to be a highly sensitive method for quantifying changes in rock properties such as Young's modulus, as well as for modelling the change in crack density and saturation occurring in a rock mass with time.     

Sectional velocity model for microseismic source location in tunnels

Microseismic (MS) source location is the foundation of MS monitoring and warning. The accuracy of MS source location depends on the accuracy of the velocities used in the location algorithm. In this work, a suitable sectional velocity model for MS source location in tunnels is proposed. In the model, the velocities from the MS source to the MS sensors in any one group are almost the same but those to different groups of MS sensors may be different. An efficient global optimization algorithm (particle swarm optimization) is applied to search for the MS source location and sectional velocity. Results from a tunnel simulation show that the velocities obtained using the sectional velocity model are close to the actual ones and location accuracy is greatly improved. The average location error is reduced by 78.3% (from 13.05 to 2.83 m). The proposed model was applied to MS source location in the deeply-buried tunnels of the Jinping II hydropower station in China. The case shows that the sectional velocities obtained are in accordance with the geological conditions. The locations of rockburst and MS events in the rockburst development process are clustered in the actual rockburst area. The method is good for rockburst monitoring and warning in the tunnels. In addition, the impact of error in the velocity on MS source location accuracy in tunnels is discussed. In tunnels, error in velocity is found to have a great impact on MS source location accuracy.     

基于MSFM的复杂速度岩体微震定位研究

快速精准的微震震源定位方法是微震监测技术更好地发挥岩体稳定性预测预警作用的基础。精确的初至波走时计算是提高微震定位精度的关键。针对实际工程中带有空洞和速度分区的复杂波速岩体,引入速度快、精度高和对复杂模型适应性强的多模板快速行进法multi-stencils fast marching methods(MSFM)用于初至波走时计算。该方法利用坐标旋转的方式生成新的计算模板,使网格对角邻点参与计算,提高了the Fast Marching Method(FMM)在对角方向的计算精度。首先,对比分析了一、二阶FMM和MSFM计算精度和效率,表明二阶MSFM具有更高的计算精度;其次,在分层速度岩体和带空洞岩体中分别采用单一速度模型和二阶MSFM计算初至波走时,通过与解析解对比发现,二阶MSFM较单一速度模型的计算绝对误差平均减小了97.65%和95.18%;然后,建立速度分层且带有隧洞的岩体模型,验证了二阶MSFM算法对复杂速度模型适应性极强的特点;最后,提出了基于MSFM的复杂速度岩体微震定位算法,并将其应用到白鹤滩水电站左岸边坡微震定位。通过对现场采集的4个爆破事件进行定位试算,得到使定位误差平均值最小(9.6 m)的相对最优层速度组合并用于考虑空洞的速度模型构建,爆破事件走时正演验证了本速度模型的可靠性。对2015年5月的128个微震事件分别采用单一速度模型和提出的定位算法进行定位,通过对比定位效果,发现后者定位的事件较前者在岩体主要损伤区(层内错动带LS331和LS337)附近有更明显呈条带状分布的聚集现象。研究表明MSFM算法作为走时正演方法具有很好的应用价值,提出的基于MSFM的微震定位方法能够有效地提高震源定位精度。     

声发射定位的稳健算法

 针对岩石力学实验声发射三维定位常规算法精度较低的问题,分析各种改进的定位算法。通过使用波速均匀的样品进行人工触发声发射实验发现,随机误差是岩石实验中声发射定位不准的最主要因素。为消除随机误差,采用最小绝对偏差法进行定位。绝对偏差最小法是一种适合于存在离群点时的稳健估计算法,可以克服最小二乘法仅在误差为正态分布时才有效的缺点。实验结果表明,与最小二乘法相比,当数据中存在个别误差较大的离群点时,采用最小绝对偏差法可以使得定位精度得到明显改善。     

基于小波变换时频能量分析技术的岩石声发射信号时延估计

声发射源定位技术是根据各传感器接收声发射信号的时差来实现损伤定位的,时延估计精确程度直接影响声发射源定位的精度。首先,在对不同损伤的声发射波形模式和频率识别的基础上,利用小波变换提取相应的单一频率或某一很窄频率段内的波形,并据此实现不同传感器在该频段的时延估计,为声发射源定位提供一个更为科学的方法;然后,使用Hyperion超声波系统,对单轴加载条件下岩石破裂过程中的声发射信号进行监测,并使用仪器自带的定位算法实现声发射源定位;最后,基于小波变换的方法对岩石试样声发射信号的时频能量分布特征进行分析,实现声发射源定位,并将定位结果与试样的真实破裂模式进行比较。试验结果表明,基于小波变换时频能量分析技术有利于减小声发射源定位的误差,从而提高材料损伤定位的精度。     

顾及粗差的最佳曲面迭代拟合方法探讨

在数据处理中经常遇到拟合问题,但拟合所采用的数据往往又存在系统误差或粗差,如何区分拟合函数模型误差和拟合数据粗差是值得讨论的问题。本文基于现有的粗差拟准检定法(QUAD)探测粗差准确的优点和判断函数模型的准则理论,提出一种顾及粗差的迭代拟合方法,先确定曲面拟合的函数模型,在此基础上进行粗差探测并剔除,然后进一步进行曲面拟合,以达到曲面函数优选的目的。最后以GPS高程异常拟合为例进行验证,得到了预期的结果。     

相对运动法与绝对位移直接求解法算法误差分析

多点激励地震响应分析过程中,相对运动法和绝对位移直接求解法分别假定阻尼与内部节点相对速度、绝对速度成比例,由于阻尼假定的不一致,计算结果可能存在误差.采用随机振动分析方法对瑞利阻尼模型下2种求解方法计算结果之间的误差进行了理论分析,得出了2种算法下结构动态响应功率谱密度误差主要受激励频率与结构基频的比值、结构阻尼比影响...     

Back-analysis of rock mass strength parameters using AE monitoring data

Most back-analyses in geotechnical engineering are based on methods that utilize field displacement monitoring data. In the present study, a novel method is developed to back-calculate rock mass strength parameters from AE (acoustic emission) monitoring data in combination with FEM stress analysis. The method is based on the important concept of generalized AE initiation threshold of rock masses, established from comprehensive data analysis of laboratory test and underground monitoring programs using AE and microseismic (MS) techniques. An easy-to-use Wizard is developed in Microsoft Excel™ to assist site engineers to perform the back-analysis. The efficient solver in Excel is utilized to reach the optimization solution of an objective function with constraints. The Wizard allows the user to complete the analysis process in an interactive fashion. One example is given to demonstrate the back-analysis process using AE monitoring data recorded from a cavern site. The rock mass strength parameters identified from this approach compare well with field test data, suggesting that the tool can be used effectively to back-calculate rock mass strength parameters from AE monitoring data.     

基于VFOM的矿山微震震源定位及近震震级标定

矿山微震事件震源位置和近震震级是矿震最基本的参数,其准确计算对矿震事件分析与信息挖掘具有重要作用。介绍了一种有别于传统定位思路的定位方法—虚拟场优化法(virtual field optimization method,VFOM),并给出了以台站计算震级偏差最小为目标的近震震级公式回归方法。将VFOM和近震震级参数回归方法用于开阳磷矿用沙坝矿区401个微震事件的震源定位和近震震级公式的重新标定。结果表明,定位结果可靠,重新标定震级公式得到的震级台站偏差相比于现有公式有明显的减小。此外,采用标定震级公式计算的震级分布观察到了明显的双峰分布现象,表明用沙坝矿的微震数据可能由两种成因的事件构成。实例表明,不同地区的近震震级计算公式必须根据实测数据重新标定,否则将可能丢失一些重要的震级分布特征。     

Estimation of convergence of a high-speed railway tunnel in weak rocks using an adaptive neuro-fuzzy inference system(ANFIS) approach

Estimation of tunnel diameter convergence is a very important issue for tunneling construction,especially when the new Austrian tunneling method(NATM) is adopted.For this purpose,a systematic convergence measurement is usually implemented to adjust the design during the whole construction,and consequently deadly hazards can be prevented.In this study,a new fuzzy model capable of predicting the diameter convergences of a high-speed railway tunnel was developed on the basis of adaptive neuro-fuzzy inference system(ANFIS) approach.The proposed model used more than 1 000 datasets collected from two different tunnels,i.e.Daguan tunnel No.2 and Yaojia tunnel No.1,which are part of a tunnel located in Hunan Province,China.Six Takagi-Sugeno fuzzy inference systems were constructed by using subtractive clustering method.The data obtained from Daguan tunnel No.2 were used for model training,while the data from Yaojia tunnel No.1 were employed to evaluate the performance of the model.The input parameters include surrounding rock masses(SRM) rating index,ground engineering conditions(GEC) rating index,tunnel overburden(H),rock density(?),distance between monitoring station and working face(D),and elapsed time(T).The model’s performance was assessed by the variance account for(VAF),root mean square error(RMSE),mean absolute percentage error(MAPE) as well as the coefficient of determination(R2) between measured and predicted data as recommended by many researchers.The results showed excellent prediction accuracy and it was suggested that the proposed model can be used to estimate the tunnel convergence and convergence velocity.     

全站仪三角高程法桥墩沉降观测的尝试

本文分析了全站仪中点单觇法测定三角高程的误差,提出了消除和减小误差的实用方法,给出了一些有益的结论。     

PSO优化ELM在火灾探测中的应用

为提高火灾探测精度,避免标准ELM陷入局部最优,本文基于火灾特征值CO浓度、烟雾浓度、温度建构了一种基于粒子群(PSO)优化极限学习机(ELM)的火灾探测模型,通过PSO优化ELM输入层与隐含层权值以及偏置,利用最优值进行极限学习机网络训练,将训练好的网络对测试样本进行预测并验证方法有效性.研究显示,PSO-ELM的均...     

Acoustic emission detection of fatigue damage in cruciform welded joints

Weld seams are critical points for the initiation of fatigue cracks in steel structures subjected to cyclic loads. Semi-elliptical surface cracking at the toes of a fillet weld is not easily found when it is partially through the thickness and subcritical. In this study the acoustic emission (AE) method is used to detect crack propagation in cruciform fillet welded joints that are representative of typical fatigue sensitive details in steel bridge superstructures. The effect of geometry and fatigue load on the AE data is investigated by varying the width of the base plate and the stress ratio. AE data filtering based on load pattern, source location, and waveform feature analysis was implemented to minimize noise-induced AE signals and false indications due to wave reflections. AE time domain features such as amplitude (b-value), counts, signal strength, and absolute energy are employed to study the influence of geometry and fatigue load on the AE data.     

工程结构中的阻尼与复振型地震响应的完全平方组合

对工程结构中阻尼矩阵的简化处理途径做了简要评述 ,指出目前常用的比例阻尼理论对于小阻尼结构是适用的。但是随着机械阻尼器在结构工程中的广泛应用 ,结构的阻尼矩阵不再满足可以按照相应无阻尼结构振型解耦的条件 ,此时的振型是由实部和虚部组成的复数形式。由于缺乏基于反应谱的复振型地震反应叠加分析方法 ,也是为了简单起见 ,在抗震设计规范中建议采用强迫解耦的近似分析方法。文中对强迫解耦方法的基本概念和适用性进行了探讨 ,指出在一般情况下这一方法是可以接受的 ,但是对于过阻尼和其它特殊情况 ,误差也是比较大的。为了避免这样的误差 ,可以采用文中推荐的基于复振型的完全平方组合 (CCQC)方法。与目前常用的CQC法相比 ,文中建议的CCQC法是按照同样的假定在复振型条件下推导出来的近似分析方法 ,完全避免了复数运算 ,表达方式也一样简单实用 ,因此很适合在实际工程和抗震设计规范中应用。此外文中还讨论和介绍了在比例阻尼和非比例阻尼条件下如何将CQC和CCQC方法加以推广应用于多维地震输入的情况     

算子识别反问题模型优化与数据优化的联合反演技术

针对算子识别反问题,分析了解的不适定性与模型误差、数据误差的关系,建立了基于模型优化和数据优化的联合反演技术,提出了适合同时处理数字式数据与非数字式数据的量化单调消噪方法。建立了数值反演可靠性概念,包括正演算子可靠性、正演计算可靠性、测量设计可靠性、反演算法可靠性、反演计算可靠性、测量数据可靠性,并建立了相应的可靠性定量评估方法。通过一个岩土工程的算子识别反问题的工程应用与数值试验说明:其一,这一联合反演技术实质是一门系统性的优化技术,能够显著提高数值反演的可靠性和准确度;其二,应用可靠性定量评估方法,能够客观地、定量地获得反问题解估计的质量评定。     

Prediction of shield tunneling-induced ground settlement using machine learning techniques

Predicting the tunneling-induced maximum ground surface settlement is a complex problem since the settlement depends on plenty of intrinsic and extrinsic factors. This study investigates the efficiency and feasibility of six machine learning (ML) algorithms, namely, back-propagation neural network, wavelet neural network, general regression neural network (GRNN), extreme learning machine, support vector machine and random forest (RF), to predict tunneling-induced settlement. Field data sets including geological conditions, shield operational parameters, and tunnel geometry collected from four sections of tunnel with a total of 3.93 km are used to build models. Three indicators, mean absolute error, root mean absolute error, and coefficient of determination the (R²) are used to demonstrate the performance of each computational model. The results indicated that ML algorithms have great potential to predict tunneling-induced settlement, compared with the traditional multivariate linear regression method. GRNN and RF algorithms show the best performance among six ML algorithms, which accurately recognize the evolution of tunneling-induced settlement. The correlation between the input variables and settlement is also investigated by Pearson correlation coefficient.     

Spatial climate variation pattern and regional prediction of rainfall in Jordan

Currently Jordan is facing various water problems accompanied by rapid population growth, urbanisation and industrialisation. It is of outmost importance to search for water resources augmentation possibilities leading to decision‐making procedures by addressing the rainfall sources as the main water resources in Jordan, through refined techniques. Point cumulative semivariogram (PCSV) samples are analysed in order to identify the regional dependence of the rainfall phenomena. Amman station is taken as a pivot site because of its location in the centre of the Kingdom, where the samples of the PCSV are calculated for eight systematic directions. Standard regional dependence function (SRDF) is obtained from the sample PCSV and the weighted average procedure is applied with the help of SRDF to predict the rainfall amounts. The radius of rainfall influence is determined for Amman in each direction. The cross‐validation methods are used to predict the rainfall in Amman using different samples representing along each direction. The result of cross‐validation method is acceptable in all samples with relative error not exceeding 10%, except in the desert sides where larger errors indicate weak regional dependence.     

基于高密度台阵的小尺度区域微震定位研究

准确的震源定位是微震研究的基础。针对微震定位误差较大的情况,探究了台阵密度同定位误差之间的联系。通过建立了立体监测体系模型,以到时差为变量建立目标方程,采用粒子群算法进行定位求解,研究了定位方法、波速误差和震源位置对定位的影响;根据现场试验,分析了台阵密度对定位的影响。研究发现,波速误差对定位误差有着极大影响,且定位波速过小带来的误差更大;台站包络范围内的定位效果好于外部,波速误差越大,效果越明显。台阵密度对定位的影响体现在两方面:第一,台站阵面数量,定位精度从高到低依次是多阵面,近震源单阵面,远震源单阵面;第二,台站的数量,采用多阵面定位时,震源定位误差同台站数量呈负指数相关。研究成果可以为矿山微震监测和中小尺度微震的研究提供一定的参考作用。     

基于地表移动矢量的概率积分法参数反演方法

为解决概率积分法参数反演时计算不稳定、初值依赖、优化指标难以选取、非矩形工作面,多工作面影响下难以反演的问题,提出采用地表空间移动矢量反演概率积分法参数的遗传算法模型。该模型采用地表移动矢量的误差平方和最小作为计算指标,以遗传算法作为参数优化的核心算法进行概率积分法参数反演。用空间移动矢量指标可以解决分别采用下沉、水平移动监测值反演结果不相同、精度难以估算的难题。矢量反演模型对观测站设置没有特别严格的要求,降低了设站不当引起的计算误差。为解决遗传算法多次计算结果不同的问题,建立了组合预测计算方法,依据中误差加权均值得到唯一的计算结果。基于矢量移动值的反演模型,避免了传统计算方法的多个缺陷,计算效率高、易于与已有开采沉陷预计程序结合,为解决非矩形、多工作面地表移动观测站参数反演的工程应用问题提供了新的解决思路和计算方法。     

A multi-camera based photogrammetric method for three-dimensional full-field displacement measurements of geosynthetics during tensile test

Conventional methods for measuring the deformational response of geosynthetics, such as the linear variable differential transformers (LVDTs), strain gauges, and extensometers have several limitations in fully determining the complete strain distribution in geosynthetics. This paper presents a multi-camera based photogrammetric method to track the 3D full-field displacements of geosynthetics during tensile tests. The proposed method extends the conventional one-camera based photogrammetry for static object measurements to multi-camera-based photogrammetry for object measurements with continuous movements or deformations. It is non-contact, cost-effective, highly accurate, and capable of measuring the 3D full-field displacements of the geosynthetics. A tensile test on a geogrid specimen was performed to verify the effectiveness and accuracy of the proposed photogrammetric method. The results from the tensile tests using both the proposed method and conventional methods, such as machine-controlled displacement measurements and extensometer, were presented and compared. It was observed that the average absolute difference between the proposed photogrammetric method and the machine-controlled movements of the bottom clamp was 0.25%, and the average absolute error was 0.038 mm. The average difference in measurements made by the proposed method and extensometer was 0.07%. It was further found that the proposed method can provide more comprehensive input, such as the complete strain and modulus distributions in the geosynthetics, for a probability-based geosynthetics design.