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。     

基于希尔伯特—黄变换的超高层建筑模态参数识别

基于改进的希尔伯特-黄变换(HHT)即结合随机减量技术(RDT)的HHT对7～9级风力作用下,超高层建筑--上海金茂大厦的加速度响应现场实测数据进行分析与处理,以识别出上海金茂大厦东西和南北方向的第1、2阶自振频率及相应的阻尼比.在识别中,为了避免结构模态的混叠现象,本文引入了巴特沃斯带通滤波器来对加速度实测数据实行滤波处理.识别结果显示:上海金茂大厦东西方向和南北方向的第1阶自振频率近似相等,但是东西方向和南北方向的第2阶自振频率相差较大;结构东西和南北方向的阻尼比皆小于结构材料的阻尼比,而且随着模态阶数的增大识别出的阻尼比标准差呈现增大的趋势.这些研究结果对未来超高层建筑的设计具有借鉴意义.同时,识别结果也表明,HHT+RDT+巴特沃斯带通滤波器方法可以有效地识别出超高层建筑的模态参数.     

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.     

基于短时傅里叶变换的快速贝叶斯模态参数识别方法

为反映结构非平稳响应信号的时频特性，提出基于短时傅里叶变换的快速贝叶斯模态参数识别(FBST)方法。该方法采用短时傅里叶变换代替傅里叶变换进行模态参数识别，使模态参数的识别同时具有时频特性，同时能够给出识别结果的不确定性。利用时域分解解耦技术，将多自由度多模态响应信号转变为单自由度单模态响应信号以提升计算效率，推导得到高信噪比下负对数似然函数的表达式。采用数值算例验证了FBST方法在时变频率和阻尼比识别上的有效性。在此基础上，针对某大跨柔性光伏支架结构气弹模型的风洞试验数据和某高层建筑风振实测加速度响应数据，利用FBST方法识别了对应结构的阻尼比、频率，并与连续小波变换和Hilbert-Huang变换等经典方法的识别结果进行对比。数值算例分析结果显示，对于时变、非时变信号，FBST方法均能识别与理论值较为一致的阻尼比和频率结果。对于大跨柔性光伏支架结构的气弹试验数据和高层建筑实测加速度响应，FBST方法识别得到的频率结果与连续小波变换以及Hilbert-Huang的结果较为一致，而识别出的阻尼比存在较大变异系数。     

网架模型结构模态分析的试验研究

实验模态分析是综合运用线性振动理论、动态测试技术、数字信号处理和参数识别等手段,进行系统识别的过程。模态分析是有效的结构检测和安全评估的方法之一,它是根据测量模态参数(固有频率、阻尼比、振型、模态刚度、模态质量)相对于正常值产生的变化,并通过相关分析与识别来判断结构安全程度的一种先进方法。本文通过对网架模型结构进行试验模态分析,研究了试验模态技术在实际运用中的试验方法,识别系统的模态参数并与有限元分析进行比较,有限元结果与实测频率有一定的不同,但前四阶模态频率的差值百分比均在9%以内,说明实测的结果与有限元分析是比较吻合的。     

改进贝叶斯谱密度法及其在超高层结构振动模态参数识别中的应用

基于白噪声激励的贝叶斯谱密度识别方法,可在识别出结构模态参数的同时,对识别结果的不确定性进行评估。在贝叶斯谱密度法(BSDA)的基础上,进一步提出适合有色噪声激励的改进参数识别方法(MBSDA),并对参数已知的合成信号进行参数识别。通过两种方法识别出的阻尼比、荷载等主要参数指标的对比表明,MBSDA比BSDA有较高的准确性。对位于深圳市高280 m的超高层建筑在近5年4次台风作用下的加速度响应时程进行参数识别,并评估结果的不确定性。结果表明:采用MBSDA和BSDA对结构频率进行识别,二者结果基本一致,但前者识别得到的模态阻尼比略高于后者;由4次台风作用下的加速度响应识别得到的阻尼比和结构振动加速度均方根之间不存在明显的统计相关性,所测超高层建筑的平均阻尼比为1.02%。     

识别结构模态阻尼比的一种新方法

提出一种新的由结构自由振动响应识别结构阻尼比的方法。对于单自由度振动系统 ,推导出响应历程与时轴所围各面积之间的确定性关系后 ,利用各面积之间的关系来确定自由衰减振动的阻尼比系数。与传统的对数衰减率法比较 ,它具有抗噪声干扰能力强、精度高、稳定性好及简便实用等特点。对于多自由度振动系统 ,先将结构上某测点的自由振动响应表达为一理论解析式x (t) ,以eat相乘x (t) ,预给a初值范围 ,通过牛顿二分法(或黄金分割法 )搜索a值 ,直至eatx (t)做等幅振荡 ,则该阶模态的各模态参数得以确定。从总响应中扣除该阶模态对总响应的贡献后 ,重复这一过程 ,则可识别出响应信号中各阶模态的模态阻尼比。仿真计算与岳阳洞庭湖斜拉桥拉索实测试验结果表明了本文方法的有效性和实用性。     

基于HHT和WT识别高层建筑模态参数的比较研究

现役高层建筑动力响应的实测与参数识别对结构动态数据资料的补充和设计准确性的校验是十分必要的.首先回顾了基于HHT和WT识别结构动力参数的基本原理;接着,基于高层建筑动力响应的实测数据进行了结构固有频率和阻尼比的识别.结果表明,对结构固有频率和低阶阻尼比的识别两者都具有较高的准确性;而对于高阶阻尼比的识别,两者有较大差别.对于固有频率呈密集分布结构的动力参数识别,WT方法通过调整小波中心频率而实现频率分离,因而WT方法更为简单有效.     

消能减震建筑结构的附加有效阻尼比估计

为估计一栋实际消能减震建筑结构在地震作用下的附加有效阻尼比,提出了一种基于有限元模型修正技术的阻尼比估计和验证方法。考虑到结构初始有限元模型存在较大模型误差,采用基于结构振动模态参数的直接模型更新方法修正初始有限元模型,其中,对于实测振型不完整问题,利用振型扩阶方法补充完整振型。基于模态应变能概念,利用整体结构模态参数识别值,推导了油阻尼器支撑系统附加给结构的有效阻尼比和有效频率的计算公式,并估计了主体结构的频率和阻尼比。以一组实际地震动监测数据为例,采用建议方法估计有效阻尼比和有效频率,通过对比修正模型的预测响应与实际监测数据,验证了建议方法的有效性。     

大跨度圆竹拱结构动力测试及有限元模型修正

为深入研究圆竹结构的结构动力性能,以2019年北京世界园艺博览会国际竹藤组织馆为对象,研究其大跨度圆竹拱结构的动力特性.采用现场实测的试验方法对该圆竹拱结构进行动力测试,获得了该结构加速度响应信号,采用峰值拾取法与随机子空间识别法对响应信号进行分析并获得了该结构的固有频率、振型及阻尼比.同时,基于实测模态参数对该圆竹拱...     

考虑土-结构动力相互作用的框架结构的参数识别研究

对一座采用柱下独立基础的钢筋混凝土4层框架结构进行了随着层数增加的4种工况模态实验,用脉冲锤击法测试得到了各种工况的整体模态频率和振型。考虑地基-基础-上部结构动力相互作用,上部框架结构采用缩聚得到的弯剪结构模型,下部基础利用Pais等人提出的弹性地基上埋置矩形板的地基阻抗函数进行简化处理得到的计算模型。在满足地基动剪模量和各层混凝土的弹性模量随框架层数的增加而增加的原则下,建立了4种工况下的多目标优化准则。将基于频率数据识别欠定问题的灵敏度方法进行了结构物理参数以及地基参数同时识别,识别得到的模态实验值与测试值符合良好。识别结果能够反应地基基础对结构的影响并为进一步损伤诊断提供了依据。     

大跨度空间膜结构随环境风速模态变异性分析

由于膜结构具有较强的几何非线性特性,同时受流固耦合效应的影响使其动力参数识别难度加大,基于此点,本文利用小波包、随机减量技术和Laplace小波联合方法对大跨度空间膜结构的模态参数进行了基于实测数据的识别,并进一步分析了大跨度空间膜结构模态参数随风速的变化规律及其相关性,分析结果显示,该方法可有效识别膜结构的动力参数,且具有较好的抗噪能力,对于骨架支撑式膜结构而言,由于存在气动阻尼作用,其结构自身总阻尼较常规结构为大,这有利于结构气动稳定性,但该种结构并不属于风致敏感性结构。     

Modal parameter identification of Tsing Ma suspension bridge under Typhoon Victor: EMD-HT method

This paper aims to identify the natural frequencies and modal damping ratios of the Tsing Ma suspension bridge during Typhoon Victor using the newly emerged empirical mode decomposition (EMD) method in conjunction with the Hilbert-transform (HT) technique. Stationary tests on the acceleration responses of the bridge recorded at different locations and in different directions during Typhoon Victor are first carried out to classify the recorded response data. Natural frequencies and modal damping ratios identified by the EMD-HT method are then compared with those obtained by the traditional fast Fourier transform (FFT)-based method. The modal parameters identified by the EMD-HT method from the bridge responses recorded at different locations are compared with each other to check their consistency. Furthermore, the variations of natural frequency and total modal damping ratio with vibration amplitude and mean wind speed are examined. The results demonstrated that the EMD-HT method is applicable to modal parameter identification of large civil structures under typhoons. The EMD-HT method and the FFT-based method produced almost the same natural frequencies but the FFT-based method gave higher modal damping ratios than the EMD-HT method in general.     

Monitoring Structural Health Using a Probabilistic Measure

A Bayesian probabilistic methodology for structural health monitoring is presented. The method uses a sequence of identified modal parameter data sets to continually compute the probability of damage. In this approach, a high likelihood of a reduction in model stiffness at a location is taken as a proxy for damage at the corresponding structural location. The concept extends the idea of using as indicators of damage the changes in model parameters identified using a linear finite-element model and modal parameter data sets from the structure in undamaged and possibly damaged states. This extension is needed because of uncertainties in the updated model parameters that in practice obscure health assessment. These uncertainties arise due to effects such as variation in the identified modal parameters in the absence of damage, as well as unavoidable model error. The method is illustrated by simulating on-line monitoring, wherein specified modal parameters are identified on a regular basis and the probability of damage for each substructure is continually updated. Examples are given for abrupt onset of damage and progressive deterioration.     

环境振动下的钢管混凝土拱桥试验与分析

环境振动试验是检测大型桥梁结构的主要方法,检测得到的模态参数是判定桥梁健康状况的重要依据.本文基于随机振动理论,从雁滩黄河大桥在环境激励下获得的加速度测试信号中提取高信噪比的响应信号,采用频域峰值法和时域随机子空间法识别得到了该桥的固有频率、阻尼比和振型等模态参数,并与有限元模型计算结果进行了对比,验证了识别结果的可靠...     

Uncertainty quantification of structural flexibility identified from input–output measurement data for reliability analysis

In contrast to the traditional uncertainty quantification of the modal parameters identified from the output-only measurement data, this study develops an uncertainty propagation and quantification method for structural flexibility identified from input–output measurement data and then uses the derived flexibility matrix for structural reliability analysis. First, a novel procedure for variance estimations of the complete system matrix of the state-space model is derived based on first-order perturbation theory. Then, the mode scaling factors and integrated modal flexibility are subsequently derived and quantified. Finally, the predicted displacements and their uncertainty intervals are used to implement the reliability analysis in terms of the structural displacement serviceability limit state (SLS). The accuracies of the derived expressions are verified by a numerical example through the comparison of variance values estimated from Monte Carlo simulations. The simulation example also indicates that we can expect to identify structural parameters with higher reliability if the input force to the structure is measured, and the identified modal scaling and corresponding flexibility matrix undergo more uncertainty than those of the modal parameters. Finally, we apply the proposed uncertainty quantification method to a scaled three-story frame structure to demonstrate its practicability. The proposed method bridges a gap between the identified structural flexibility and structural reliability analysis directly by the probability category.     

NExT-ITD方法在振动台模型参数识别中的研究

本文详细介绍了NEx T方法(Natural Excitation Technique,NEx T)和ITD方法(Ibrahim Time Domain,ITD)的理论基础,并对方法实现过程中可能出现的问题进行了探讨,在此基础上编制了计算分析程序,用该方法成功识别了一座3层框架振动台实验模型结构的模态频率和阻尼比,并结合试验现象对结果进行了准确性和有效性验证。结果表明该方法可准确识别结构模态参数,可供结构健康监测、损伤识别及抗震分析等工作参考使用。     

On‐line system identification of structures using wavelet‐Hilbert transform and sparse component analysis

A new wavelet‐Hilbert transform based sparse component analysis (WHT‐SCA) method is presented for online system identification in indeterminate conditions. The instantaneous phase ratios of output signals are obtained by using a wavelet‐Hilbert transform based filter; and the out‐of‐phase data, that causes errors in identification accuracy, is detected and eliminated. Then, modal parameters of the structure are identified through existing relationships between the dispersion of filtered data in the frequency domain. Subsequently, to demonstrate the capability of the online identification, a new controller is introduced by combining the WHT‐SCA and a semi‐active tuned mass damper (STMD), resulting in creation of smart structures. The performance of the proposed method and controller is investigated through examples. The results demonstrate that, modal parameters of structures are identified accurately even with noise contamination and limited number of sensors. Also, the STMD is effectively robust against any variations in modal parameters of the structure.     

Modal identification of Di Wang Building under Typhoon York using the Hilbert–Huang transform method

The Di Wang Building is one of the tallest composite buildings in the world, located in downtown Shenzhen City of China about 2 km from the Hong Kong border. On 16 September 1999, Typhoon York – that is the strongest typhoon since 1983 and the typhoon of longest duration on record – attacked Hong Kong and Shenzhen. The wind and structural monitoring system installed in the Di Wang Building timely recorded wind and structural response data. The newly emerged Hilbert–Huang transform (HHT) method in conjunction with the random decrement technique (RDT) is applied to the measured data in this paper to identify dynamic characteristics of the building. A series of natural frequencies and modal damping ratios of the building under different wind speeds in different directions are identified and compared with those from the fast Fourier transform (FFT)‐based method. The variations of natural frequency, total modal damping ratio and net structural modal damping ratio with wind speed and vibration amplitude are also investigated. The results show that the natural frequencies identified by the HHT method are almost the same as those obtained by the FFT‐based method. The first two modal damping ratios given by the HHT method are, however, lower than those by the FFT‐based method, which may indicate that the FFT‐based method overestimates the modal damping ratios. Both the total and the net structural modal damping ratios increase with increasing wind speed and vibration amplitude but the situation is reversed for the natural frequency. Copyright © 2003 John Wiley & Sons, Ltd.     

大型推土机推土刀板模态分析

本文采用随机锤击法进行激励，对大型推土机刀板进行模态试验，并用正交分量法识别模态参数，获取了刀板作业状态下的固有频率，因有振型，模态阻尼比等动态特性。这些参数可用来进一步计算刀板的动态响应及动态应力。