随机子空间法参数识别与有限元分析

随机子空间法是近些年来发展起来的一种线性系统识别方法,可以有效地从环境激励的结构反应中获取模态参数。属于时域的方法,这种时域识别方法基于状态空间模型,仅利用结构输出反应,避免了传统的人工识别和迭代过程。它不仅可以识别结构的频率,而且可以识别结构的阻尼和振型。介绍了随机子空间的理论,用该方法对一框架模型进行参数识别,通过与有限元识别结果的比较证明了随机子空间方法不失为一种有效的模态参数识别方法。     

高耸柔性结构的模态参数识别及模型修正研究

采用三种基于环境激励的模态参数识别方法(多参考点稳定图算法(M-NExT/ERA)、数据驱动随机子空间识别法(SSI/Data)和增强频域分解法(EFDD))对广州新电视塔(GNTVT)进行模态参数识别,得到前12阶模态参数。利用有限元软件ANSYS建立GNTVT的有限元模型,根据识别得到的实测模态参数,结合遗传算法对GNTVT有限元模型进行修正。结果表明:识别方法可靠,得到的结果具有较好的精度;修正方法前5阶模态具有较好效果,满足工程需要。     

桥梁风洞试验模态参数识别的随机子空间方法

模态参数识别是桥梁风洞试验中的一项重要内容,发展了基于参考点、无需输出协方差估计的识别振动系统模态参数的随机子空间方法,其识别精度和可靠性通过数值算例验证。对状态空间理论中的稳定图作了全面的阐释。根据苏通大桥和苏拉马都大桥主梁三自由度节段模型风洞试验采集到的位移信号,采用随机子空间方法识别了侧弯、竖弯和扭转模态频率和阻尼比,并且与随机搜索方法识别结果进行对比。分析结果表明,随机子空间方法和随机搜索方法识别结果非常吻合,本文发展的随机子空间方法是识别风洞试验桥梁模态参数的一种有效和实用方法。     

随机子空间法在海上风电结构模态参数识别中的应用

频率、阻尼比等是海上风电结构动力分析的重要设计参数.但是,环境激励下海上风电结构实测振动响应噪声水平高、信噪比低,应用传统随机子空间方法(SSI)进行海上风电结构模态参数识别十分困难.对海上风电高桩承台基础进行现场测试,并对环境激励下海上实测数据进行模态参数识别,旨在获取结构频率及阻尼信息.为提升模态参数识别精度,应用奇异值分解技术实现模型定阶,模型阶次得到了合理确定;同时,应用稳定图分析技术,噪声模态得到有效识别.结果表明:结合模型定阶与稳定图分析技术,随机子空间法可以比较准确地获得环境激励下的海上风电基础结构的频率及阻尼信息.     

基于地震记录和SSI方法的高土石坝模态识别

采用实测地震记录来识别高土石坝的模态参数是进行大坝动力特性研究的一种可行的方式。根据地震中坝体监测点记录的数据构建协方差驱动的随机子空间模型(stochastic subspace identification, SSI),通过构造多个不同维度的Hankel矩阵来形成稳定图,可以很好地剔除虚假模态,形成较清晰的稳定轴,采用谱系聚类的筛选方法,不仅可以有效地识别坝体的固有频率和阻尼比,而且实现了物理模态参数的自动识别,规避了人为选择引入的误差。通过两个数值算例验证了提出的随机子空间法应用于地震数据分析的有效性和精度,并将其应用于糯扎渡心墙堆石坝的模态参数识别,获得了合理的坝体固有频率和阻尼比,表明该方法可以较好地识别出坝体的模态参数,具有很好的工程应用,可以为高土石坝抗震安全有限元分析提供一定的依据和参考。     

环境激励下房屋建筑的阻尼比识别

阻尼比的准确取值一直是结构动力分析的难点,由于阻尼机理非常复杂,对阻尼比的取值一般通过实测得到。传统的模态参数识别方法需要同时利用激励和响应信号,但对实际建筑结构,激励施加存在困难。探讨了基于环境激励下的模态识别方法,利用环境激励(如施工机械振动、风、车辆、行人、地脉动等)下的结构振动响应数据,采用随机子空间(Stochastic Subspace Identification)法,有效地识别实际建筑结构的模态参数的方法。工程实例的模态参数识别结果表明,该方法不仅能准确识别出结构的模态频率,还能相对准确地得到结构的模态阻尼比。     

基于随机子空间识别的损伤试验研究

采用附加质量模拟损伤的方法通过对三层空间钢框架模型模态试验分析,采用随机子空间(SSI)法进行模态参数的识别,并在模拟健康状态和有损伤状态下识别结果与有限元模态分析及经典的特征值实现法(ERA)结果进行多次对比,对比结果表明了随机子空间法识别模态参数的可靠性。依据随机子空间法识别的模态振型,结合模态置信准则损伤判别的方法,进行了损伤的诊断,诊断的结果判断了结构的损伤程度,搜索出了损伤的最不利工况。     

车辆荷载作用下简支梁桥动力特性分析及模态参数识别

为研究车辆荷载作用对简支梁桥结构动力性能的影响,对车辆荷载作用下的简支梁桥进行能量分析并采用随机子空间法(SSI)和RDT-STD法对简支梁桥进行模态参数识别研究。分析不同车速激励下的桥梁能量分布情况,对比不同模态参数识别方法的频率、阻尼和振型的识别结果。结果表明:随着车速的增加,简支梁桥的加速度幅值不断增大,能量向高频段偏移,更容易激发结构的高阶模态;随机子空间法(SSI)和RDT-STD法均能有效识别出简支梁桥的竖向频率,SSI法对于简支梁桥频率和阻尼的识别精度高于RDTSTD法,但两种识别方法对阻尼的识别相对误差较大,且存在一定的离散性。     

基于环境激励的双曲拱桥模态参数识别

为了比较现有模态参数识别算法的优劣,分别采用随机子空间(SSI)法、特征系统实现算法(ERA)、复指数法、随机减量法(ITD)、STD法、ARMA模型时间序列法对一钢筋混凝土双曲拱桥的模态参数进行识别。结果表明:SSI法、ERA法、复指数法、ITD法、STD法、ARMA模型时间序列法,准确度均较高,可用于实际工程结构模态频率识别;几种时域模态参数识别方法的阻尼比识别结果离散性较大,无法准确估计结构的阻尼比。     

框架结构模态参数识别时域方法的比较研究

通过对4层钢框架模型试验得到环境激励下的位移响应,运用ITD、STD、复指数法、ERA、随机子空间法等5种时域方法来识别结构的模态参数,从而验证了5种方法在结构参数识别中应用的可行性。5种方法对频率的识别比较精准,对阻尼比的识别精度相对较差。通过与试验数据对比,同时对大量数据的处理发现,随机子空间法和ERA法对模态参数的识别最为精准,STD法和复指数法次之,ITD法的识别精度较差。     

Modal parameter identification for closely spaced modes of civil structures based on an upgraded stochastic subspace methodology

Based on a recently developed stochastic subspace identification methodology equipped with an alternative stabilization diagram and a hierarchical sifting process, this research aims to improve this approach for more efficiently identifying the modal parameters of civil structures with closely spaced modes. The concept of a doubly folded stabilization diagram is proposed to combine the advantages of both the conventional and alternative stabilization diagrams for achieving better computational efficiency. In addition, the hierarchical sifting process is further refined to more properly handle closely spaced modes. The investigated cases for the occurrence of extremely close modes in civil engineering structures include axially symmetric stay cables, a symmetric cable-stayed bridge with respect to the pylon, and a uniformly arranged office building. Applying the upgraded SSI methodology established in this study, it is demonstrated that the modal parameter identification of civil engineering structures with extremely close modes can be elevated to an advanced level with a frequency space index at the order of 0.1%. Such an accurate identification and distinction is particularly important in the practical applications of structural health monitoring to prevent the false alarms resulting from the confusion of two extremely close modes. Furthermore, this approach also performs well in the determination of mode shape vectors for closely spaced modes to provide an excellent tool for observing their corresponding orthogonality property and high sensitivity.     

基于AEEMD和改进DATA-SSI算法的桥梁结构模态参数自动化识别

模态参数作为桥梁结构最重要的动力参数之一,在实际运用中,可通过监测其变化情况来辨识结构的使用性能,精确地参数识别对保障桥梁健康运营具有十分重要的意义。鉴于此,该文对现阶段常用的振动信号降噪处理算法和模态参数识别算法进行了相应的改进。一方面,提出一种新的信号自适应分解与重构算法,即自适应总体平均经验模态分解算法（AEEMD）,该算法相比总体平均经验模态分解算法（EEMD）而言,能够根据信号的自身特征自动化确定添加白噪声的幅值标准差和集成平均次数|能更好地处理端点效应|同时还能够保证所得本征模态函数之间不存在模态混叠现象|最终实现有效IMF分量的自动化筛选和信号重构。另一方面,将多维数据聚类分析算法引入随机子空间算法中,并以频率值、阻尼比以及振型系数为因子建立判别矩阵,以智能化区分虚假模态和真实模态,最终实现模态参数自动化识别。文章最后分别用模拟信号和实际桥梁测试信号对所提算法的有效性进行验证,结果表明,该文所提算法能运用于实际桥梁结构的模态参数自动化识别。     

基于环境激励的连续梁桥挠度评定方法研究

为研究基于环境激励的在役连续梁桥承载能力评定方法的可行性,根据《公路桥梁荷载试验规程》设计桥梁静载试验方案,利用随机子空间法测量识别桥梁在环境激励下的模态参数,结合桥梁有限元模型提取集中质量矩阵,对桥梁实测模态振型进行质量归一化,识别桥梁的实测位移柔度矩阵,预测桥梁在静力荷载作用下的实测模态挠度,最后结合规范对桥梁承载能力进行评定。以4跨连续梁桥为实例建立损伤桥梁有限元模型,基于有限元数值模拟环境激励,预测了该连续梁桥的柔度矩阵和试验荷载下的模态挠度,并与初始无损桥梁的理论设计挠度进行对比,计算了静载试验校验系数。结果表明:各测点挠度的最大相对误差不超过6%,基本满足工程精度要求,根据规范判断该损伤桥梁承载能力不满足设计要求; 该方法能够准确评估既有桥梁的承载能力,基于环境激励的连续梁桥承载能力评定方法具有较强的有效性和可行性。     

Modal Identification Study of Vincent Thomas Bridge Using Simulated Wind-Induced Ambient Vibration Data

Abstract:   In this article, wind-induced vibration response of Vincent Thomas Bridge, a suspension bridge located in San Pedro near Los Angeles, California, is simulated using a detailed three-dimensional finite element model of the bridge and a state-of-the-art stochastic wind excitation model. Based on the simulated wind-induced vibration data, the modal parameters (natural frequencies, damping ratios, and mode shapes) of the bridge are identified using the data-driven stochastic subspace identification method. The identified modal parameters are verified by the computed eigenproperties of the bridge model. Finally, effects of measurement noise on the system identification results are studied by adding zero-mean Gaussian white noise processes to the simulated response data. Statistical properties of the identified modal parameters are investigated under an increasing level of measurement noise. The framework presented in this article will allow us to investigate the effects of various realistic damage scenarios in long-span cable-supported (suspension and cable-stayed) bridges on changes in modal identification results. Such studies are required to develop robust and reliable vibration-based structural health monitoring methods for this type of bridge, which is a long-term research objective of the authors.     

Control mode selection for modal control of long-span arch bridge

For seismic control of arch bridge, a model reduction of long-span arch bridge was implemented based on modal analysis. As for the critical mode selection, an approach based on the maximum modal displacement was presented. This approach takes into consideration the effect of external seismic excitation and is more reasonable than only considering dynamic bridge characteristics based on a modal contribution ratio. The time domain and frequency domain analysis method were used to verify the simplified model of the Nimu arch bridge in Tibet as an example. The numerical results show that the method of maximal modal displacement better analyze long-span arch bridge when multisupport seismic excitation must be considered. The reduced-order system also is more in line with the performance of the original model.     

Operational Modal Parameter Identification from Power Spectrum Density Transmissibility

Abstract: Operational modal analysis subjected to ambient or natural excitation under operational conditions has recently drawn great attention. In this article, the power spectrum density transmissibility (PSDT) is proposed to extract the operational modal parameters of a structure. It is proven that the PSDT is independent of the applied excitations and transferring outputs at the system poles. As a result, the modal frequencies and mode shapes can be extracted by combing the PSDTs with different transferring outputs instead of different load conditions where the outputs from only one load condition are needed. A five‐story shear building subjected to a set of uncorrelated forces at different floors is adopted to verify the property of PSDTs and illustrate the accuracy of the proposed method. Furthermore, a concrete‐filled steel tubular half‐through arch bridge tested in the field under operational conditions is used as a real case study. The identification results obtained from currently developed method have been compared with those extracted from peak‐picking method, stochastic subspace identification, and finite element analysis. It is demonstrated that the operational modal parameters identified by the current technique agree well with other independent methods. The real application to the field operational vibration measurements of a full‐sized bridge has shown that the proposed PSDTs are capable of identifying the operational modal parameters (natural frequencies and mode shapes) of a structure.     

Control mode selection for modal control of long-span arch bridge

For seismic control of arch bridge, a model reduction of long-span arch bridge was implemented based on modal analysis. As for the critical mode selection, an approach based on the maximum modal displacement was presented. This approach takes into consideration the effect of external seismic excitation and is more reasonable than only considering dynamic bridge characteristics based on a modal contribution ratio. The time domain and frequency domain analysis method were used to verify the simplified model of the Nimu arch bridge in Tibet as an example. The numerical results show that the method of maximal modal displacement better analyze long-span arch bridge when multisupport seismic excitation must be considered. The reduced-order system also is more in line with the performance of the original model.     

Assessment of SSI on the longitudinal seismic response short span bridges

Current practice usually neglects the effects of soil-structure interaction (SSI) in the seismic analysis and design of bridges. This work attempts to assess the significance of SSI on the seismic response of short span bridges. The focus is placed on pier behaviour, since piers together with the abutments are the most critical elements in securing the integrity of bridge superstructures during earthquakes.

The study is based on a simple representation of a soil-bridge pier system, yet one able to capture the effects of the most significant physical parameters. It has been found that SSI greatly affects the dynamic behaviour of bridge piers leading to more flexible systems, increased damping and larger total displacements. Besides a thorough investigation of the relative significance of various physical parameters of the system response, an easy-to-use approach that can be incorporated for a preliminary design of bridges concurrent with the AASHTO specifications is presented. The study concludes that safer and more economical bridge designs can be obtained by properly accounting for SSI.     

Spurious mode distinguish by modal response contribution index in eigensystem realization algorithm

Modal identification process has played an important role for civil engineering structures. Among the identification methods, eigensystem realization algorithm is one of the most popular one. However, the noises in practical environment can influent the effectiveness of eigensystem realization algorithm, which can introduce spurious modes due to the overestimated physical order for the structure. This paper proposes a new index named the modal response contribution index (MRCI) for the eigensystem realization algorithm, which can determine the structural physical order and then distinguish spurious mode more precisely. First, the structural responses are divided into different modal response by the well‐known modal superposition theory. Then the square root summation of each modal response is obtained and named as MRCI. A modified stabilization diagram is also presented, which increases the row number of Hankel matrix with the determined order by MRCI. The straight lines formed by the stable points in the modified stabilization diagram designate the structural modal parameters. Finally, one numerical example and the monitoring data of a practical cable‐stayed bridge are employed. The results show that the proposed MRCI and modified stabilization diagram can identify the structural physical mode more precisely.