复杂追踪算法结合EEMD识别结构损伤

结构损伤会引起结构振动信号的突变,而该突变信号会淹没于环境噪声信号中。为此,文章将复杂追踪理论(CP)引入结构损伤识别领域,将损伤识别问题转化为突变特征提取问题。提出一种复杂追踪结合集合经验模态分解(EEMD)识别结构损伤的新方法,首先采用EEMD预处理结构振动信号,接着将分解得到的本征模函数(IMF)作为混合信号输入CP模型中,提取出包含损伤特征的本征模函数,进而识别出结构损伤发生的时刻及位置。最后,通过对环境激励下六自由度质量-弹簧系统和地震激励下三层框架模型的数值分析。结果表明,该方法能够准确有效地识别结构损伤异常时刻与位置。     

基于HHT的非线性结构系统识别研究

本文研究基于HHT的多自由度非线性结构系统识别方法。首先通过EMD分解得到结构的非线性模态(NNM),然后对非线性模态进行H ilbert分析,识别出结构的瞬时特征参数(瞬时振幅、瞬时固有频率等),进而由各参数间关系识别出非线性结构的类型。最后通过一个具有非线性刚度的两自由度剪切型建筑结构的数值模拟验证了该方法的有效性。     

基于偏最小二乘线性求解的结构损伤识别

基于模态参数化线性求解结构损伤的识别方法在工程中具有较为广泛的应用。然而，在噪声的干扰下，当结构可测量的模态阶数较少时，利用该方法求解的结果会出现大量的虚假损伤，严重扰乱真实的损伤信息。针对此问题，引入了一种基于偏最小二乘多线性回归建模的方法来对损伤识别结果进行降噪处理。通过对损伤结构的频率和振型信息添加一定水平的噪声干扰，分析确定结构单元的损伤参数，并利用偏最小二乘法重构线性方程组。同时，选择识别结果较为稀疏的解作为标准样本点，利用奇异值分解法回代求解结构的损伤参数。以桁架模型为例的数值模拟结果表明，在噪声干扰下，该方法与传统最小二乘法和奇异值分解法相比，不仅损伤识别结果准确，而且能够最大程度抑制虚假损伤的产生。     

基于应变模态法识别刚架桥梁的损伤

基于应变模态方法，对刚架桥的损伤识别进行了研究。通过对某刚架桥在不同损伤工况下的数值仿真计算，探讨了应变模态方法用于刚架桥损伤识别的能力。计算结果表明：利用应变模态差曲线能比较准确地识别出刚架桥的损伤位置；应变模态差曲线在刚架桥损伤单元处的跳跃幅值随单元损伤程度的增加而增大，依此可定性地识别出刚架桥的损伤程度。     

基于损伤部位向量法的钢框架损伤识别研究

对损伤部位向量(DLV)法作了简单介绍,并用该方法对钢框架进行了损伤识别和损伤定位。该方法假定结构损伤前后为线性,对结构损伤前后柔度矩阵差进行奇异值分解,将奇异值为零所对应的向量,作为静荷载施加在无损结构的测点位置,则应力为零的单元为可能损伤的单元。对3种不同工况的钢框架进行了振动模态试验,用前3阶模态参数构造框架的柔度矩阵,按照DLV法对其进行了损伤识别,识别结果与已知损伤情况相一致。从测试自由度不完备、噪声和振型质量归一化系数这3个方面对识别效果进行了分析,结果表明:当损伤使结构动力特性有微小改变时,使用该方法不易定位损伤,应结合局部损伤识别方法进行判定;当损伤使结构动力特性有较大改变时,该方法能有效识别损伤的单元。DLV方法概念简单,理论明确,不受结构类型的限制,不需要结构的数学模型和模型缩聚或扩展技术,只需获得结构损伤前后的前几个低阶模态参数,即可识别结构一处或多处损伤,实际应用时可操作性强。     

基于EMD方法与RBF神经网络的结构损伤检测

针对结构损伤检测中损伤的识别、定位以及程度的标定这三个独立并按一定先后顺序进行的检测过程,提出了一种能将以上三者同时进行的联合检测方法。该方法首先利用经验模态分解(EMD)方法将三层钢筋混凝土剪切型结构在各种损伤工况下的顶层地震作用加速度响应分解为若干固有模态函数(IMF)分量,然后以此IMF分量和未经EMD分解的原始加速度响应数据来构造损伤标识量,作为特征参数依次输入到径向基函数神经网络(RBFNN)中进行损伤检测。给出了应用此方法的具体步骤,通过仿真实验证明了利用该方法进行结构损伤一次检测的可行性和有效性,结果表明,由加速度响应经EMD分解而得到的IMF分量输入到RBFNN中能够更为精确地一次检测出结构所有损伤信息,并且RBFNN在结构损伤损度大时具有更好的检测效果。     

基于摄动有限元方法对梁结构损伤的识别

结构损伤的定量识别是工程技术中急待解决的问题。利用矩阵摄动和结构有限元动力学理论推出梁结构损伤程度定量识别的公式和方法,该方法仅需要在役结构的固有频率测量值就可识别结构的损伤位置和损伤程度,而且可以识别结构的老化程度,避免了由模态振型识别损伤,因测量自由度不足带来的误差,通过对一钢悬臂梁损伤识别的数值仿真,证明了该方法的有效性。该方法具有较大的工程应用价值。     

基于峰值位移均值识别非线性结构的损伤

目前对结构进行损伤识别的方法大多基于结构振动信号的变化而进行，不同振动信号在不同环境下的损伤识别能力各不相同。为验证振动信号在随机环境下的的识别效果，以随机振动理论为基础，针对非线性结构的损伤识别问题，提出了利用结构峰值位移均值进行损伤识别的新方法。该方法不需要结构损伤前的模态参数。通过对两种不同类型非线性结构的数值模拟分析，对该方法进行了验证。结果表明，该方法能够有效识别结构的单处损伤、多处损伤以及损伤程度，充分显示了该指标检测损伤的准确性和敏感性。     

基于曲率模态曲线的结构损伤识别方法

采用曲率模态对简支梁的单处和多处损伤进行了识别研究。首先用ANSYS有限元程序建立模型,并计算得到了位移模态振型;针对噪声下具有不同损伤状况的结构,进行了曲率模态分析,通过曲率模态曲线的畸变定位损伤位置,然后利用最小二乘拟合法计算了损伤处的有效面积,并估计了其损伤程度。数值分析表明:曲率模态对结构的损伤较敏感,它无需原始结构的模态参数,仅需低阶模态信息便可准确方便的识别结构的损伤位置,识别过程中在引入随机误差情况下各指标识别效果的比较结果表明,所提方法能有效估计损伤程度,可为今后结构损伤识别提供参考。     

改进曲率模态识别桥梁损伤位置方法研究

结构健康监测和结构状态评估的主要前提之一是结构损伤识别。基于曲率模态对结构局部损伤比较敏感和频率指标测试简单方便、精度高的特点,本文提出了一种以结构的曲率模态为基础,综合考虑频率的变化的改进的结构损伤识别方法。随机子空间方法是一种行之有效的基于环境激励的结构状态识别方法。该方法的主要优点是无需人工激励,不中断桥梁的运营。为此,论文提出了一种不中断桥梁运营的基于改进曲率模态的桥梁结构损伤识别方法。最后用一三跨连续梁的有限元模型对该改进方法进行了验证。结果表明,采用随机子空间结合改进的曲率模态方法可以在不中断桥梁运营的前提下有效地识别出桥梁的损伤状况。     

Structural identification with incomplete output‐only data and independence of measured information for shear‐type systems

Structural identification is the inverse problem of estimating physical parameters of a structural system from its vibration response measurements. Incomplete instrumentation and ambient vibration testing generally result in incomplete and arbitrarily normalized measured modal information, often leading to an ill‐conditioned inverse problem and non‐unique identification results. The identifiability of any parameter set of interest depends on the amount of independent available information. In this paper, we consider the identifiability of the mass and stiffness parameters of shear‐type systems in output‐only situations with incomplete instrumentation. A mode shape expansion‐cum‐mass normalization approach is presented to obtain the complete mass normalized mode shape matrix, starting from the incomplete non‐normalized modes identified using any operational modal analysis technique. An analysis is presented to determine the minimum independent information carried by any given sensor set‐up. This is used to determine the minimum necessary number and location of sensors from the point of view of minimum necessary information for identification. The different theoretical discussions are illustrated using numerical simulations and shake table experiments. It is shown that the proposed identification algorithm is able to obtain reliably accurate physical parameter estimates under the constraints of minimal instrumentation, minimal a priori information, and unmeasured input. The sensor placement rules can be used in experiment design to determine the necessary number and location of sensors on the monitored system. John Wiley & Sons, Ltd.     

Bridge health monitoring system based on vibration measurements

A bridge health monitoring system is presented based on vibration measurements collected from a network of acceleration sensors. Sophisticated structural identification methods, combining information from the sensor network with the theoretical information built into a finite element model for simulating bridge behavior, are incorporated into the system in order to monitor structural condition, track structural changes and identify the location, type and extent of damage. This work starts with a brief overview of the modal and model identification algorithms and software incorporated into the monitoring system and then presents details on a Bayesian inference framework for the identification of the location and the severity of damage using measured modal characteristics. The methodology for damage detection combines the information contained in a set of measurement modal data with the information provided by a family of competitive, parameterized, finite element model classes simulating plausible damage scenarios in the structure. The effectiveness of the damage detection algorithm is demonstrated and validated using simulated modal data from an instrumented R/C bridge of the Egnatia Odos motorway, as well as using experimental vibration data from a laboratory small-scaled bridge section.     

传感器布设中有效独立法的简捷快速算法

本文提出一个通过正交三角分解快速计算有效独立法系数的方法。有效独立法是传感器布设中影响最广泛的一种方法,它使目标模态尽可能线性独立。传统的有效独立法计算需要对信息阵进行特征值分解或者计算矩阵逆,计算量较大。本文在笔者以前得出的有效独立法与模态动能法关系的基础上,提出先通过对模态矩阵进行正交三角分解（QR）,然后比较其行范数即可得到有效独立法的系数,进而对各待选传感器位置进行排序并迭代依次删除。在待选传感器位置比感兴趣的模态数较多时,该法的计算效率明显提高。同时,采用正交三角分解删除一行后的更新算法,进一步提高了迭代计算的效率。最后通过I-40桥的算例表明该法的有效性。     

川南地区砖混结构房屋典型震害及地震易损性研究

以川南地区为研究区,并以在建造方式上具有明显当地地域特征的砖混结构房屋为研究对象,结合砖混结构房屋建造特点及川南历史地震(如长宁6.0级地震)震害调查结果等,分析砖混结构房屋典型震害特征,统计其在不同烈度下不同破坏等级的比例,采用经验分析法得到初步的易损性矩阵。在此基础上,针对因样本局限性造成的结构在高烈度下破坏比例不全,使实际易损性矩阵缺失的问题,通过插值法,推算高烈度下的破坏比例,补全经验易损性矩阵,拟合出易损性曲线,建立以震害统计为主、数值模拟为辅的砖混结构易损性分析模型;并基于平均震害指数对比分析,对易损性分析的可靠性进行检验。结果表明,构建的易损性矩阵能客观反映川南地区砖混结构房屋的抗震能力,对开展震害预测、灾害损失评估及震害风险评估等工作具有实际应用价值。     

基于小波包能量特征向量的结构动力响应损伤识别

在结构动力响应监测中如何准确判断结构损伤状况是工程上的一大难题,本文研究通过小波包能量特征向量提取结构损伤信息来识别结构损伤的方法,并进行实验分析,同时分析噪声对能量值的影响。实验发现:小波包能量特征向量具有识别结构状态的能力,并且不受噪声的影响,相反,对观测信号去噪后不利于能量特征向量的提取。     

Modal model identification of structures under unmeasured seismic excitations

Techniques developed for structural identification of a structural model are typically based on information regarding the response and the forcing actions. However, in some situations it can be necessary, or simply useful, to refer only to the measured responses. In this paper we describe a technique suitable for identifying the modal model of a spatial frame in the frequency domain when the seismic input is unknown both in time contents and direction. In some previous theoretical works we established that this identification problem has a unique solution when at least three time‐history responses are known. Here numerical techniques are developed which allow the evaluation of the modal quantities in practice. Numerical applications are carried out on plane and spatial framed structures by using a modal model which may be complete, including all the structure's modes, or incomplete, including only the lowest modes. In most cases the obtained results are satisfactory. Copyright © 2005 John Wiley & Sons, Ltd.     

System identification of linear structures based on Hilbert–Huang spectral analysis. Part 2: Complex modes

A method, based on the Hilbert–Huang spectral analysis, has been proposed by the authors to identify linear structures in which normal modes exist (i.e., real eigenvalues and eigenvectors). Frequently, all the eigenvalues and eigenvectors of linear structures are complex. In this paper, the method is extended further to identify general linear structures with complex modes using the free vibration response data polluted by noise. Measured response signals are first decomposed into modal responses using the method of Empirical Mode Decomposition with intermittency criteria. Each modal response contains the contribution of a complex conjugate pair of modes with a unique frequency and a damping ratio. Then, each modal response is decomposed in the frequency–time domain to yield instantaneous phase angle and amplitude using the Hilbert transform. Based on a single measurement of the impulse response time history at one appropriate location, the complex eigenvalues of the linear structure can be identified using a simple analysis procedure. When the response time histories are measured at all locations, the proposed methodology is capable of identifying the complex mode shapes as well as the mass, damping and stiffness matrices of the structure. The effectiveness and accuracy of the method presented are illustrated through numerical simulations. It is demonstrated that dynamic characteristics of linear structures with complex modes can be identified effectively using the proposed method. Copyright © 2003 John Wiley & Sons, Ltd.     

苏通大桥结构健康状态评估技术研究与应用（3）：主梁损伤定位

为提高基于模态参数的损伤识别方法的损伤敏感性和噪声鲁棒性,将多源数据融合技术引入到苏通大桥主梁损伤定位方法中。基于D-S证据理论对模态柔度和模态应变能指标进行数据融合,并以苏通大桥扁平钢箱梁为分析对象,对融合后损伤定位指标的应用效果进行了讨论。结果表明：基于数据融合的损伤定位方法具有较强的损伤敏感性,只需要较少的低阶模态信息就能识别主梁的早期损伤;数据融合后,损伤定位指标可以在较强的噪声环境下准确地识别斜拉桥钢箱梁的损伤,具有较好的工程实用性。