协方差驱动随机子空间算法的梁桥模态参数识别

基于状态空间系统识别理论和算法,对随机子空间识别算法的特性,适用性及其在桥梁模态参数识别中的应用进行了研究。首先由QR分解计算由系统输出组成的Hankel矩阵,并构建基于输出的自协方差Topelitz矩阵,再对该矩阵进行奇异值分解（SVD）,获取系统的可观测矩阵及可控制矩阵,依据协方差驱动的随机子空间算法构建结构离散状态矩阵并进行特征值分解,从而识别结构的模态参数。编制了协方差驱动随机子空间算法识别桥梁结构模态参数的M atlab程序,以某三跨连续梁桥梁的模态参数识别为例,验证了方法的可靠性和可行性。结果证明,协方差驱动随机子空间算法可应用于实际桥梁的模态参数识别中。     

延拓小波变换识别的桥梁模态参数研究

振动系统模态识别是当今桥梁结构动力特性研究的热点之一。从复模态理论的一般阻尼系统的模态参数分析入手,利用径向神经网络插值技术,对含有噪声的振动信号进行信号预测延拓降噪处理,借助连续的Morlet小波变换,识别出了振动结构系统的模态。以重庆大佛寺长江大桥为研究背景,使用模态叠加法和Morlet小波分析识别结构,二者吻合程度较高。研究结果表明,基于径向神经网络的延拓预测的信号降噪效果好;Morlet小波变换识别模态参数精度满足工程要求。     

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.     

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。     

连续梁桥模态参数识别的随机子空间方法

简要介绍了协方差随机子空间方法,在此基础上,采用一等截面连续梁桥作为算例,通过ANSYS程序进行建模分析,对该连续梁桥进行识别,讨论了系统阶次的选择对识别结果的影响。     

基于模态曲率与小波变换的网壳结构损伤识别研究

结合模态曲率与小波变换的方法对网壳结构的损伤识别进行研究。以一网壳结构的缩尺模型为例进行数值分析,假设结构35号杆件的截面出现刚度折减的轻微损伤,以模型损伤前后的模态曲率作为损伤指标进行连续小波变换,从而判断结构的损伤位置。数值分析的结果表明,利用模态曲率的小波变换系数差可以粗略定位损伤,而利用曲率模态差值的小波变换系数可以较为准确地定位损伤,且分析及数据处理过程更为简便可靠,可见基于模态曲率与小波变换的损伤识别方法对于网壳结构的损伤定位是非常有效的。     

基于AFDD的悬索桥模态参数识别

运营状态下模态参数识别是掌握结构在服役期间状况的有效手段,运营期间通过长期监测系统得到的数据量十分庞大,现有频域方法虽然都能较精确地识别到结构模态参数,但是人为干预过多,且主观性强,对密集模态识别效果欠佳,对庞大数据处理费时费力等缺点。为解决此问题,文章以频域分解法为基础,引入尺度空间方法,对奇异值曲线进行尺度空间缩放,进而识别较为密集的模态信息,最终形成具有峰值自动拾取的AFDD法。并以一大跨度悬索桥实测数据为依托,验证了方法的可行性与高效性。     

基于随机子空间结合稳定图的拱桥模态参数识别方法

为了避免目前常用的结构模态参数识别方法容易出现虚假模态等缺陷,提出了一种将随机子空间法与稳定图法相结合的模态参数识别方法。通过随机子空间法有效地从环境激励的结构响应中获取模态参数,通过稳定图方法确定系统阶次。通过对稳定图方法的改进,避免了虚假模态的出现,进而提高了随机子空间方法的识别精度,并在一钢管混凝土拱桥上对这种新方法进行了验证。结果表明,该方法具有良好的识别效果。     

两座高耸结构基于RSV-150激光测振仪的环境振动实测与模态识别

针对一座高23m的特种钢结构与一座高300m的钢筋混凝土电视塔,采用RSV-150超远工作距离激光测振仪,开展了结构在环境激励下的振动实测与模态参数识别。作为一种非接触式的测量方式,激光测振仪具有操作简单、测量便捷等优点。采用了基于随机子空间方法的结构模态识别算法,对实测到的结构速度响应进行了模态分析。分析结果表明,该算法具有精度高、稳定性好的优点,可以有效地获取结构的自振频率与阻尼。选择结构的不同部位作为激光测振的反射点,对实测的自振频率影响不大,结果离散性较小。进行了结构的简化有限元分析,数值模拟获得的模态信息与实测结果之间有较好的对应性,验证了试验方法的可靠性。     

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.     

环境激励下宽频带模态参数识别研究

由于功率谱的模态阶次是频响函数模态阶次的2倍,直接使用响应信号的功率谱进行模态参数识别容易导致识别过程中需要过高的系统阶次、运算量加大、数值算法不稳定等问题。因此使用功率谱的模态识别方法多为窄频带算法,难以适用于宽频带识别。针对该问题,在使用相关图法估计功率谱的过程中,仅对正时延相关函数进行傅里叶变换(FFT)可以实现功率谱降阶,并且降阶后的模态参数不发生变化。根据频响函数与降阶功率谱具有相似数学表达式的特点,将试验模态分析中的多参考点最小二乘复频域(p-LSCF)宽频带算法与降阶功率谱相结合,实现了环境激励条件下的模态参数识别。通过一个二层单跨框架结构仿真算例与一个建筑结构的实测算例进行了验证,结果表明：该方法能够较准确识别模态参数,具有耦合模态的识别能力;在模态选择中,除了借助于模态指示函数,高阶模态应利用稳定图加以判断。     

Frequency domain identification of modal characteristics and loads from output-only measurements

This paper proposes a frequency domain framework for concurrently estimating the modal structural parameters and modal loads from the measured output response. A mathematical load model is theoretically developed and compared to the load determined by force identification. Unlike conventional modal identification schemes, the proposed approach can effectively accommodate the spectral shape of the external load in the frequency domain, enabling the determination of the modal parameters without explicit white noise assumption. The proposed approach is verified by applying it to a single-degree-of-freedom system system representing a modal response, an aeroelastic model in an atmospheric boundary layer wind tunnel, a multi-degree-of-freedom system, and the measured acceleration response of a 40-story building. The simulation results demonstrate that the proposed technique can reliably estimate the modal parameters and load model and is robust against the noise present in the response and the order of the load model. Additionally, the proposed technique can be applied to various loading conditions such as vortex-induced and buffeting effects since the modal parameters and the load model can be identified for any shape of the loading spectrum.     

Benchmarking environmental and operational parameters through eco-efficiency criteria for dairy farms

Life Cycle Assessment (LCA) is often used for the environmental evaluation of agri-food systems due to its holistic perspective. In particular, the assessment of milk production at farm level requires the evaluation of multiple dairy farms to guarantee the representativeness of the study when a regional perspective is adopted. This article shows the joint implementation of LCA and Data Envelopment Analysis (DEA) in order to avoid the formulation of an average farm, therefore preventing standard deviations associated with the use of average inventory data while attaining the characterization and benchmarking of the operational and environmental performance of dairy farms. Within this framework, 72 farms located in Galicia (NW Spain) were subject to an LCA + DEA study which led to identify those farms with an efficient operation. Furthermore, target input consumption levels were benchmarked for each inefficient farm, and the corresponding target environmental impacts were calculated so that eco-efficiency criteria were verified. Thus, average reductions of up to 38% were found for input consumption levels, leading to impact reductions above 20% for every environmental impact category. Finally, the economic savings arising from efficient farming practices were also estimated. Economic savings of up to 0.13 € per liter of raw milk were calculated, which means extra profits of up to 40% of the final raw milk price.     

Experimental study of structural damage identification based on modal parameters and decay ratio of acceleration signals

A novel damage assessment method based on the decay ratio of acceleration signals (DRAS) was proposed. Two experimental tests were used to show the efficiency. Three beams were gradually damaged, and then the changes of dynamic parameters were monitored from initial to failure state. In addition, a new method was compared with the linear modal-based damage assessment using wavelet transform (WT). The results clearly show that DRAS increases in linear elasticity state and microcrack propagation state, while DRAS decreases in macrocrack propagation state. Preliminary analysis was developed considering the beat phenomenon in the nonlinear state to explain the turn point of DRAS. With better sensibility of damage than modal parameters, probably DRAS is a promising damage indicator in damage assessment.     

Estimating aeroelastic effects from full bridge responses by operational modal analysis

This paper deals with the estimation of structural modal parameters of long-span bridges from their recorded wind-excited response, by separating structural properties from aeroelastic effects using information on the incoming wind velocity. Specific attention is devoted to structural damping ratios, as their accurate estimations are of crucial importance in bridge engineering. However, uncertainties affecting damping ratios estimates often complicate any attempt towards their accurate assessment. More importantly, in the case of long-span bridges, aerodynamic damping often hides the actual structural one, even at low wind velocities. In this paper, the use of a data-driven stochastic subspace approach, specifically conceived to eliminate, as much as possible, analyst's arbitrariness and to deal with the non-whiteness of the wind excitation, is proposed for system identification. Structural properties are then separated from aeroelastic effects via nonlinear regressions of the modal parameter estimates at different mean wind velocities. Application of this technique to field measurements and numerically simulated buffeting response data referred to a real suspension bridge is finally presented, showing its effectiveness for separating structural from aerodynamic damping in practical case studies.     

环境激励下工作模态参数识别

分析了模态参数识别的意义,对环境激励下模态参数识别的方法进行分类叙述,并对目前比较先进的几种方法的原理和特点进行了阐述,指出其各自的适用条件及存在的问题,以促进环境激励下工作模态参数识别的研究。     

Vibration-based operational modal analysis of the Mikron historic arch bridge after restoration

This research presents finite element modelling, vibration-based operational modal analysis, and finite element model updating of a restored historic arch bridge. Mikron historic bridge, constructed on F?rt?na River in Rize, Turkey, is the subject of this case study. The General Directorate for Highways of Turkey repaired the bridge's main structural elements, arches, sidewalls, and filler material in 1998. To construct a 3D finite element model of the bridge, ANSYS finite element software estimated the analytical dynamic characteristics. Induced ambient vibrations such as human walking and wind excited the model bridge to allow measurement of the bridge's responses. Enhanced frequency domain decomposition in frequency domain and stochastic subspace identification in time domain methodologies extracted experimental dynamic characteristics. A comparison of the analytical and experimental results showed significant agreement between mode shapes, but some differences in natural frequencies appeared. Consequently, updating the finite element model of the bridge by changing boundary conditions minimised the differences between analytical and experimental natural frequencies. After the finite element model updating process, the differences between natural frequencies declined from 7% to 2%.     

Investigation of a historic masonry structure by numerical and operational modal analyses

This paper presents the results of model calibration conducted on a historical mosque called Hafsa Sultan in Manisa, Turkey. The finite element model of the mosque was calibrated by the use of the results obtained from ambient vibration tests of the structure. In order to develop a solid model of the structure, the dimensions of the structure, defects such as cracks and material degradations in the structure, and the materials used in different parts were identified. For the evaluation of the material properties of the structure, nondestructive and destructive testing methods were used. The numerical and experimental modal parameters of the structure were obtained by finite element method (FEM) and Operational Modal Analysis (OMA), respectively. The natural frequencies and corresponding mode shapes were obtained from both FEM and OMA and compared with each other. While a good compatibility was achieved between mode shapes, some differences between natural frequencies occurred. It was thought that the differences resulted from variations in the Young's modulus of masonry, cracks in elements or boundary conditions. Therefore, the finite element model was calibrated by changing material parameters. Finally, a more realistic numerical model of the mosque was put forward and the results were discussed in detail. Copyright © 2015 John Wiley & Sons, Ltd.     

利用小波分析方法识别结构模态参数

在高层建筑抗震、抗风、健康监测及损伤诊断等研究中,结构模态参数是非常重要的参数之一。介绍了环境激励下基于小波分析的模态参数识别方法,并对实际结构振动响应信号进行小波分析。有效地识别了结构的固有模态参数,并同传统傅里叶变换、短时傅里叶变换的结构相比较,证实了小波分析方法在处理随机信号方面的优越性。另外,使用小波分析方法对测试信号进行降噪处理。分析结果表明,小波方法降噪能有效抑制噪音,还原真实信号。     

改进的模态曲率改变率损伤识别方法研究

研究了适用于简支梁和连续梁结构的改进的模态曲率改变率的损伤识别方法,比较了改进的模态曲率改变率法与模态曲率改变率法。对简支梁和连续梁不同损伤位置损伤程度的数值计算表明,改进的模态曲率改变率法可以准确地判断损伤位置,定性地判断同一位置处的损伤程度。