基于参数灵敏度最小的鲁棒主动控制方法

本文建立了带有参数摄动的结构状态空间模型。在此基础上，提出了基于参数灵敏度最小的鲁棒极点配置的主动控制算法，通过使闭环系统的特征值对系统参数变化不敏感来提高结构控制系统对参数摄动的鲁棒性。最后对一个单自由度结构地震作用下的控制仿真计算，证实了这种控制方法的有效性和较强的鲁棒性。     

A new dissipation model based on memory mechanism

Summary The model of dissipation based on memory introduced by Caputo is generalized and checked with experimental dissipation curves of various materials.List of symbols unidimensional stress - unidimensional strain - Q ^–1 specific dissipation function - c(t) creep compliance - m(t) relaxation modulus - c ₀ instantaneous compliance - m equilibrium modulus - (t) creep function - relaxation function - () spectral distribution of retardation times - spectral distribution of relaxation times - c ^*() complex compliance - m ^*() complex modulus - tang loss-tangent     

A robust method for microseismic event detection based on automatic phase pickers

We present a robust method for the automatic detection and picking of microseismic events that consists of two steps. The first step provides accurate single-trace picks using three automatic phase pickers adapted from earthquake seismology. In the second step, a multi-channel strategy is implemented to associate (or not) the previous picks with actual microseismic signals by taking into account their expected alignment in all the available channels, thus reducing the false positive rate. As a result, the method provides the number of declared microseismic events, a confidence indicator associated with each of them, and the corresponding traveltime picks. Results using two field noisy data records demonstrate that the automatic detection and picking of microseismic events can be carried out with a relatively high confidence level and accuracy.     

基于鲁棒线性二次算法的结构振动主动控制

线性二次控制算法在工程中得到了广泛的应用。本文提出了通过振型分解，赋予各阶振型不同权重，优化选择线性二次算法加权矩阵的方法，并采用回路传输恢复技术，设计了运用于土木工程结构主动减振的控制系统。仿真结果表明，本文方法能够有效地抑制高频噪声对输出控制力的影响。     

A robust channel network extraction method combining discrete curve evolution and the skeleton construction technique

The automatic mapping of drainage networks from terrain representation has been an interesting topic in hydrological and geomorphological modeling. However, the existing methods often suffer from high sensitivity to terrain noise or lose significant stream branches and accurate channel paths. In this paper, we propose a contour-based framework in drainage network extraction. The proposed framework incorporates discrete curve evolution (DCE) to eliminate the noise influence by dynamically segmenting the contour lines (CLs) into valley bends, and to detect the valley feature points. The skeleton construction technique is then applied to distill more accurate channel paths in complex terrain. Finally, a linking step is undertaken to generate the channel network. The proposed method was tested on a series of elevation datasets, with varied resolution, region size, and local relief. The experiments verified that the proposed method can achieve highly accurate channel networks and is robust, even in regions with high-contrast relief, and/or in cases with significant terrain noise and irregularities.     

基于特征结构配置的结构鲁棒控制算法及仿真

本文提出了结构系统的鲁棒主动控制算法，其目的是求取状态反馈控制律，在闭环系统具有希望特征值前提下，使得闭环系统特征值关于参数摄动具有最小的灵敏度。基于状态反馈特征结构配置参数化方法和矩阵特征值灵敏度分析理论，该问题转化为含有约束条件的优化问题，并给出了求解该鲁棒控制问题的算法。该方法给出了特征值灵敏度函数的参数化表示，且直接基于结构系统矩阵，故便于工程应用。三自由度层间剪切型结构地震作用下的仿真分析，表明所提方法的有效性。     

Design formulas for tuned mass dampers based on A perturbation technique

Modal properties of tuned mass damper (TMD)-structure two-degree-of-freedom (2DOF) linear systems are studied employing a perturbation technique. Using the perturbation solutions, formulas relevant to designing the TMD for various types of loading are obtained; they are expressed as a function of mass ratio, tuning ratio, damping ratio of the TMD and damping ratio of the structure. Equivalent additional dampings of the structure due to the TMD are derived for random and harmonic forces. Matched expressions of equivalent damping, which are valid for detuned, i.e. non-optimal, conditions are also presented. The stability boundary of TMD-structure systems subject to linear self-excited forces is derived in a closed form. Using the perturbation solutions, procedures for optimizing the TMD parameters for various types of loading are explained and the optimal values are derived. The formulas obtained in this study can be used with good accuracy for mass ratios less than 0.02.     

基于RBF神经网络的地震与爆破识别技术

利用天然地震震源和人工爆破震源之间信号能量分布的差异,结合RBF神经网络技术,对2类事件进行分类,具体步骤如下:使用8个带通滤波器对事件波形进行滤波,并划分为4个波形段:P波、P波尾波、S波和S波尾波,分别计算每个滤波器信道和波形段的能量特征值,以所得32个特征参数作为输入向量,利用RBF神经网络,对地震和爆破事件进行分类识别。结果表明,基于RBF神经网络的地震事件识别方法,识别率为88.1%,具有较高的准确性,可作为地震与爆破事件识别的一个重要依据。     

Controlled-source electromagnetic data processing based on gray system theory and robust estimation

We propose a novel method that combines gray system theory and robust M-estimation method to suppress the interference in controlled-source electromagnetic data. We estimate the standard deviation of the data using a gray model because of the weak dependence of the gray system on data distribution and size. We combine the proposed and threshold method to identify and eliminate outliers. Robust M-estimation is applied to suppress the effect of the outliers and improve the accuracy. We treat the M-estimators of the preserved data as the true data. We use our method to reject the outliers in simulated signals containing noise to verify the feasibility of our proposed method. The processed values are observed to be approximate to the expected values with high accuracy. The maximum relative error is 3.6676%, whereas the minimum is 0.0251%. In processing field data, we observe that the proposed method eliminates outliers, minimizes the root-mean-square error, and improves the reliability of controlled-source electromagnetic data in follow-up processing and interpretation.     

瞬变电磁长短时记忆网络深度学习实时反演方法

瞬变电磁一维反演方法对初始模型依赖大,对异常体边界反映不清晰,计算速度也难以达到实时化水平.为此,本文开展基于深度学习的瞬变电磁实时反演方法研究,提出在非观测时间段进行反演训练,而在观测时间段进行实时精细成像的瞬变电磁长短时记忆网络反演策略.以正演模拟获得的海量采样时间-视电阻率为输入数据,基于长短时记忆网络构造Seq2seq编码器-解码器模型,并针对瞬变电磁反演的问题特性,对decoder的结构进行适应性更改,同时加入Bahdanau Attention机制突出重点信息作用,获得深度-电阻率输出数据.将该反演网络应用于随机生成的数万组以上三层和五层地电模型,测试组三大衡量指标标准差均小于10%,验证了本文算法的可靠性,在此基础上,构建了接近实际的两组含局部异常体模型,将该反演网络进一步用于三维数值模拟数据,取得了对异常体边界反映清晰的成像结果,且计算速度均小于1 s.

     

Multivariate discrimination technique based on the Bayesian theory

A multivariate discrimination technique was established based on the Bayesian theory. Using this technique, P/S ratios of different types (e.g., Pn/Sn, Pn/Lg, Pg/Sn or Pg/Lg) measured within different frequency bands and from different stations were combined together to discriminate seismic events in Central Asia. Major advantages of the Bayesian approach are that the probability to be an explosion for any unknown event can be directly calculated given the measurements of a group of discriminants, and at the same time correlations among these discriminants can be fully taken into account. It was proved theoretically that the Bayesian technique would be optimal and its discriminating performance would be better than that of any individual discriminant as well as better than that yielded by the linear combination approach ignoring correlations among discriminants. This conclusion was also validated in this paper by applying the Bayesian approach to the above-mentioned observed data.     

A new two-way nesting technique for ocean modeling based on the smoothed semi-prognostic method

A new two-way nesting technique is presented for a multiple nested-grid ocean modeling system. The new technique uses the smoothed semi-prognostic (SSP) method to exchange information between the different subcomponents of the nested-grid system. Four versions of the new nesting technique are described, together with conventional one-way nesting. The performance of the different nesting techniques is compared, using two independent nested-grid modeling systems, one for the Scotian Shelf of the northwest Atlantic Ocean and the other for the Meso-American Barrier Reef System of the northwestern Caribbean Sea. Nesting using the semi-prognostic method is shown to effectively prevent unrealistic drift of the inner model, while use of the SSP method avoids unnecessary damping of small scales on the inner model grid. Comparison of the annual-mean flow field with the near-surface currents determined by Fratantoni (in J Geophys Res 106:2977–2996, 2001) from observed trajectories of near-surface drifters demonstrates the overall superiority of the nesting technique based on the SSP method.     

基于结构导向的梯度属性边缘检测技术

地震数据中的不连续性检测对于识别和刻画地下地质体边界具有重要意义.随着勘探目标向岩性油藏和复杂断块油藏的转变,解释人员需要对小断裂、微裂缝等微幅地质体边界信息进行精细刻画.常规边缘检测算子由于算法的局限性不能满足上述需求.本文通过引入能量归一化和沿层检测思想对常规检测算子进行改进,提出一种基于结构导向的梯度属性边缘检测技术.该技术通过结构张量估计得到局部地层区域的倾角和方位角,利用得到的倾角和方位角信息作为约束,使用二维边缘检测算子实现三维数据中的沿层不连续性检测.经过实际资料处理,并与结构导向方差属性对比分析,证实该方法在地层不连续性检测方面具有很好效果,检测得到的不连续性信息在细节上表现更丰富,可以作为地层横向差异和地质体边界识别的有力工具.     

基于信号子空间分解的三维地震资料高分辨率处理方法

提出了一种新的基于信号子空间分解技术的3 D地震资料高分辨率处理方法.利用信号子空间分解技术,不仅可以分离3 D地震资料中的信号和噪声,而且可以进一步根据地震同相轴的倾角不同,将混合信号进行分解得到单个同相轴信号.通过丢弃噪声子空间,只对不同信号子空间重构的信号利用谱白化技术进行高分辨率处理,然后累加所有处理结果,从而达到既提高地震资料的分辨率,又提高地震资料信噪比的目的.对合成资料和实际地震资料的处理结果表明,此法具有好的应用前景.     

基于井位的地震属性融合技术研究

在利用地震属性对储层预测的研究中,大部分理论方法主要存在利用单一属性预测储层这一缺陷,在实际应用中则存在单一属性不能正确预测储层的问题,这些问题应通过多元属性融合技术来解决,本文在已有井资料的基础上,对属性融合技术进行了研究,分析各属性对储层的影响因素,利用井位计算各地震属性融合比重,有机的结合了各属性的优点,提出了这一问题新的解决方法.实际资料的应用显示,该方法在储层预测中取得了良好的效果.     

基于卫星数据稳健分析技术统计分析新疆地区热异常与地震的关系

为探究地震活跃区域内地震与热异常的关联性,本文选取2014—2018年新疆地区发生的M_S≥4.0地震作为研究对象,利用卫星数据稳健分析技术从MODIS地表温度数据中提取出热异常,并结合热异常特点及筛选方法分析得出:研究区内提取出热异常84次,发生在热异常窗口期内的地震39次,占比46.43%。地震与热异常的对应关系表现为,随着地震震级增大,通过热异常检测到的地震所占比例逐渐增大。当M_S≥5.8时,研究区的地震发生均与热异常相关,当地震震级相同时,塔里木盆地中线以北区域的相关性高于以南地区,通过Molchan误差图表分析得出,M_S5.0对应预警距离作为阈值的检测效果较好。      

基于小波包分形和神经网络的地震与岩溶塌陷识别

本文以近年来广西地震台网中心记录的天然地震和岩溶塌陷为例,尝试利用基于小波包的分形和径向基函数神经网络技术对这两类事件的波形进行识别,以期有效地识别地震与岩溶塌陷。结果表明,基于小波包分形与神经网络相结合的事件识别方法对天然地震和岩溶塌陷事件的识别率高达89.5%,可作为识别天然地震与岩溶塌陷的一个有效方法。      

Implementation and testing of passive control devices based on shape memory alloys

Two families of passive seismic control devices exploiting the peculiar properties of shape memory alloy (SMA) kernel components have been implemented and tested within the MANSIDE project (Memory Alloys for New Seismic Isolation and Energy Dissipation Devices). They are special braces for framed structures and isolation devices for buildings and bridges. Their most important feature is their extreme versatility, i.e. the possibility to obtain a wide range of cyclic behaviour — from supplemental and fully re‐centring to highly dissipating — by simply varying the number and/or the characteristics of the SMA components. Other remarkable properties are their extraordinary fatigue resistance under large strain cycles and their great durability and reliability in the long run. In this paper, the working mechanisms of the SMA based devices are outlined and the experimental tests carried out to verify the above‐mentioned properties are extensively described. Copyright © 2000 John Wiley & Sons, Ltd.     

时频峰值滤波去噪技术及其应用

本文将时频峰值滤波(TFPF)去噪技术应用于共炮点地震资料的随机噪声压制.时频峰值滤波技术是通过频率调制将信号调制成解析信号的瞬时频率,利用解析信号的Wigner-Ville分布的峰值进行瞬时频率估计,恢复有效信号,与其它去噪方法相比,TFPF具有在较少的约束条件下压制强随机噪声的优点.本文针对实际地震资料的非线性特性,利用加窗的Wigner-Ville分布实现TFPF,使得地震信号在一个窗长内近似满足线性瞬时频率条件,减小由地震信号非线性引起的偏差.本文对共炮点地震记录做时频峰值滤波处理,滤波结果表明在地震勘探资料中存在强随机噪声的情况下,利用局部线性化处理的时频峰值滤波技术可以有效地压制地震资料中的随机噪声,恢复出湮没在随机噪声中的地震反射信号.信噪比提高3～6 dB.