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.     

Long-Term Monitoring and Identification of Bridge Structural Parameters

Abstract:   Vibration of a new concrete bridge was monitored and change in the bridge structural stiffness was identified accordingly over a 5-year period. This three-span 111-m long bridge is instrumented with 13 acceleration sensors at both the superstructure and the columns. The sensor data are transmitted to a server computer wirelessly. Modal parameters of the bridge, that is, the frequencies and the modal shapes were identified by processing 1,707 vibration data sets collected under traffic excitations, based on which the bridge structural parameters, stiffness and mass, and the soil spring values were identified by employing the neural network technique. The identified superstructure stiffness at the beginning of the monitoring was 97% of the stiffness value based on the design drawings. In the identified modal frequencies, a variation from −10% to +10% was observed over the monitoring period. In the identified stiffness values of the bridge superstructure, a variation from −3% to +3% was observed over the monitoring period. Based on the statistical analysis of the collected data for each year, 5% decrease in the first modal frequency and 2% decrease in the superstructure stiffness were observed over the 5-year monitoring period. Probability density functions were obtained for stiffness values each year. Stiffness threshold values for the collapse of the bridge under the operational loading can be determined. Then the number of years can be assessed for which the area under the proposed probability density functions is greater than the threshold value. So the information obtained in this study is valuable for studying aging and long-term performance assessment of similar bridges.     

Investigation concerning structural health monitoring of an instrumented cable-stayed bridge

In Hong Kong, a sophisticated long-term structural health monitoring system has been devised by the Highways Department of HKSAR Government to monitor the structural performance and health conditions of three cable-supported bridges. On-structure instrumentation systems for two new long-span bridges are also being implemented. The implementation of these monitoring systems highlights the necessity for developing a monitoring-based structural health evaluation paradigm for long-span bridges. This paper describes the research directed towards this that has been conducted in the Hong Kong Polytechnic University. Taking the instrumented cable-stayed Ting Kau Bridge as a paradigm, the research covers the development of an index system and a database system for monitoring data management, the modelling of the environmental variability of measured modal properties with the intention of eliminating environmental effects in vibration-based damage detection, and the feasibility of using measured modal properties from the deployed vibration sensors for structural damage identification.     

Modal Flexibility Analysis of Cable-Stayed Ting Kau Bridge for Damage Identification

Abstract:   The cable-stayed Ting Kau Bridge has been permanently instrumented with more than 230 sensors for long-term structural health monitoring. In this article, the feasibility of using the measured dynamic characteristics of the bridge for damage detection is studied. Making use of a validated three-dimensional (3D) finite element model (FEM), modal flexibility matrices of the bridge are constructed using a few truncated modes and incomplete modal vectors at the sensor locations. The relative flexibility change (RFC) between intact and damage states is then formulated as an index to locate damage. The applicability of this flexibility index for damage location in the cable-stayed bridge is examined by investigating various damage scenarios including those at stay cables, longitudinal stabilizing cables, bearings and supports, longitudinal girders and cross girders, and taking into account measurement noise in modal data. The influence of two ambient factors, that is, temperature change and traffic loading, on the damage detectability is also analyzed by approximately considering an equivalent alteration in the material and structural behaviors. It is revealed that in the absence of ambient effects the RFC index performs well for locating damage of different severities in single-damage cases. In multi-damage cases the RFC index may provide false-negative identification for damage at the members with low sensitivity. Eliminating ambient effects is requisite for reliable detection of damage at stay cables and cross girders. The capability of the RFC index for locating damage at cross girders is significantly dropped in the presence of measurement noise.     

Structural health monitoring of a cable-stayed bridge with Bayesian neural networks

In recent years, there has been an increasing interest in permanent observation of the dynamic behaviour of bridges for long-term monitoring purpose. This is due not only to the ageing of a lot of structures, but also for dealing with the increasing complexity of new bridges. The long-term monitoring of bridges produces a huge quantity of data that need to be effectively processed. For this purpose, there has been a growing interest on the application of soft computing methods. In particular, this work deals with the applicability of Bayesian neural networks for the identification of damage of a cable-stayed bridge. The selected structure is a real bridge proposed as benchmark problem by the Asian-Pacific Network of Centers for Research in Smart Structure Technology (ANCRiSST). They shared data coming from the long-term monitoring of the bridge with the structural health monitoring community in order to assess the current progress on damage detection and identification methods with a full-scale example. The data set includes vibration data before and after the bridge was damaged, so they are useful for testing new approaches for damage detection. In the first part of the paper, the Bayesian neural network model is discussed; then in the second part, a Bayesian neural network procedure for damage detection has been tested. The proposed method is able to detect anomalies on the behaviour of the structure, which can be related to the presence of damage. In order to obtain a confirmation of the obtained results, in the last part of the paper, they are compared with those obtained by using a traditional approach for vibration-based structural identification.     

Noncontact Operational Modal Analysis of Structural Members by Laser Doppler Vibrometer

Abstract:   A system that uses ambient vibration and two laser Doppler vibrometer (LDV) is developed for noncontact operational modal analysis of structural members. The system employs natural excitation technique (NExT) to generate the cross-correlation functions from laser signals, and the eigensystem realization algorithm (ERA) to identify modal parameters of structural members. To facilitate simultaneous modal identification, time-synchronization technique and construction of cross-correlation functions from ambient response of laser signals are proposed. Performance of the proposed system is verified experimentally by evaluating the consistency and accuracy of identification results in different measurement conditions. The work presented here is an extension of the previous study, where a modal-based damage detection method using LDV was formulated. In the present study, application of LDV for structural parameters identification of a combined dynamical system is proposed. A model that represents the connection properties in terms of additional stiffness and damping is developed, and its importance for structural damage detection is discussed. The study shows that the presence of simulated damage in a steel connection can be detected by tracking the modal phase difference and by quantifying the additional stiffness and damping .     

Rapid Impact Testing and System Identification of Footbridges Using Particle Image Velocimetry

The rapid impact testing of bridges contains unique advantages. For example, structural parameters, including frequency response function and structural flexibility matrix can be identified; however, additional impact‐testing instruments are required to excite a bridge, restricting the efficiency of the measurement strategy in terms of experimental cost and time. In this paper, a particle image velocimetry‐based method is proposed for the rapid impact testing and system identification of footbridges under pedestrian excitations. The proposed method has shown promising features: (1) pedestrian load is utilized for the impact excitation of footbridges, which is more convenient than the conventional impact‐testing method with additional excitation devices; (2) the human‐induced impact forces under varying jumping scenarios are calculated from image sequences of human motions acquired by a single camera with its noncontact and target‐less characteristics; and (3) both human‐induced impact forces (inputs) and structural responses (outputs) are employed to identify more modal parameters (i.e., scaling factors, modal mass, and structural flexibility). The robustness of the proposed method was successfully validated by a laboratory test of a simply supported beam and field testing of a cable‐stayed footbridge. The proposed method not only could improve the testing efficiency of footbridges, but also could obtain more modal parameters, which can be further utilized for deflection prediction, damage detection, and long‐term performance evaluation.     

Development of performance assessment tools for a highway bridge resulting from controlled progressive monitoring

As highway bridges continue to deteriorate given the increased service life, increase in vehicle demand and exposure to harsh environmental climates, new methods of monitoring their in situ performance are of high priority. Damage within the structure can alter various load demand and capacity characteristics, affecting the overall integrity of the bridge. Discussed in this paper is the monitoring of a simple span bridge superstructure under various induced damage states. Strain measurements were recorded at the midspan and north abutment of each girder. Six levels of damage progression were implemented at a rocker bearing and various diaphragms to girder connections. Transverse load distribution factors (DFs) and neutral axis (NA) locations were measured for each damage case and evaluated against the baseline undamaged response. These measurements serve to provide a possible method of damage detection using load-testing parameters already employed by various transportation agencies. Next, a performance index (PI) is developed for this stringer/multi-girder bridge utilising the NA and DF response from the steel girder system and the allowable stress design load-rating data. The ratio of NA to DF was compared to the inventory load rating for each girder at each damaged state. The data were fitted with a power regression model to form the PI. Furthermore, a 95% prediction interval was used around the predicted response to capture all the data from the testing. The model was applied to the damaged structure as well as two additional stringer/multi-girder bridges. The objective of the PI is to complement existing qualitative assessment protocols with quantitative results for improving the condition assessment process.     

悬索桥损伤指标的适用性分析

依据精细的悬索桥有限元模型,分析比较了在无噪声情况下频变比指标、模态曲率差指标和静态应变差指标对悬索桥不同位置损伤的适用性.对主梁和吊索两种常见损伤类型的数值模拟发现,主梁损伤时,由于各阶指标之间信息的互补性,模态曲率差指标识别效果最好;吊索损伤则对结构整体频率的影响极其微小,无法用频变比指标来定位,此时静态应变差指标最为敏感.在试验的基础上,提出了根据损伤类型来综合运用频率变化比、主梁竖弯振型模态曲率变化以及静态应变差进行悬索桥的损伤定位的方法.     

大跨度非对称悬索桥振动基频的参数敏感性分析

为了研究大跨度非对称悬索桥的动力特性,基于ANSYS软件建立了某大跨度主缆不等高支承悬索桥的三维有限元模型。在计算自振频率时考虑了表征结构非对称的参数,进行了前20阶模态分析,并分析了矢跨比、结构非对称参数、加劲梁抗弯刚度及主塔抗弯刚度等关键结构参数对其振动频率的影响。研究结果表明：不同的参数对非对称悬索桥振动基频的敏感性不同,一阶竖弯和扭转频率随矢跨比的增大减小,相对于正对称的振动频率,反对称的频率对矢跨比参数更敏感;非对称悬索桥的一阶反对称竖弯和扭转基频不受非对称结构参数的影响,而正对称竖弯和扭转基频随非对称结构参数的增大而减小;一阶横弯的自振频率对加劲梁刚度的变化非常敏感,当加劲梁的抗弯刚度增加到原来的3倍时,结构原有的振型次序发生了改变,但主塔抗弯刚度参数的变化对结构各向频率的影响很小,研究结果可为非对称悬索桥的结构设计和动力分析提供参考。     

基于振型参数的装配式桥梁损伤识别研究

利用结构动力特性的振型参数对桥梁进行快速损伤诊断和定位,可以提高结构性能评价与损伤诊断的效率。本文以装配式预应力混凝土T梁为算例,通过定义位移振型和曲率振型的桥梁损伤识别指标进行损伤识别,计算结果表明采用位移振型和曲率振型的方法进行损伤识别和定位效果较好。     

铁路简支梁桥下部结构健康状态动力评估方法研究

提出一种以实测横桥向整体振动、横桥向局部振动和顺桥向局部振动模态的不同组合为输入,采用模型修正技术和优化算法识别铁路简支梁桥下部结构的物理参数,从而实现对墩身、基础和支座病害进行定位和定量分析的动力学方法。进一步,建立了针对下部结构系统中各构件的评估准则和评估流程。对两座铁路桥梁进行现场试验,并依据所提评估方法和评估准则对其健康状态进行评估,理论分析结果现场评估结果一致,从而证明所提方法的准确性和有效性。     

Multi-source information fusion applied to structural damage diagnosis

This study aims to import multi-source information fusion (MSIF) into structural damage diagnosis to improve its validity. Two structural damage identification methods based on MSIF are put forward, one of which is to fuse two or more structural damage detection methods by MSIF and another of which is the improved modal strain energy method by multi-mode information processing based on MSIF. Through a concrete plate experiment it is proved that, if two methods are integrated by character-level information fusion, structural initial damages can be more accurately identified than by a single method. In a simulation of a concrete box beam bridge, it is indicated that the improved modal strain energy method has a nice sensitivity to structural initial damages and a favorable robusticity to noise. These two structural damage diagnosis methods based on MSIF have good effects on structural damage identification and good practicability to actual structures.     

Dynamic reduction-based structural damage detection of transmission tower utilizing ambient vibration data

This paper reports a feasibility study of utilizing ambient vibration data measured from a limited number of sensors in the structural damage detection of transmission towers, which are large-scaled three-dimensional spatial structures. To develop a practical and efficient structural damage detection methodology, the characteristics of transmission towers are considered in the development stage, including the most common types of damage, accessible locations for installing sensors, the technique needed to identify a reliable set of modal parameters utilizing ambient vibration data, a method to divide the transmission tower into sub-structures for structural damage detection, a way to formulate the damage detection problem, and the corresponding solution method. The proposed methodology is numerically verified by simulated noisy data from a three-dimensional transmission tower sample under both single and multiple damage cases. Very encouraging results are obtained, showing that the proposed methodology can identify the damaged sub-structure by estimating the ‘equivalent’ stiffness reduction even in the presence of both measurement noise and modeling error.     

Web-Based Structural Health Monitoring of an FRP Composite Bridge

Abstract:   To develop an understanding of the long-term performance of fiber reinforced polymer (FRP) composite bridge structures, a health monitoring scheme utilizing wireless technology was implemented on the Kings Stormwater Channel Bridge. The bridge, which is located on a major state highway in California, utilizes FRP composite girders and deck panels. The data collected by a comprehensive array of sensors are transmitted wirelessly, and processed in real-time remotely. Computer-based automated analysis algorithms process the incoming data to provide an assessment of structural response. Effects, due to time-based deterioration, and irregularities are determined using modal parameters, in terms of damage localization indices and an estimated damage severity. The results, made available via a web-based interface, enable appropriate action to be authorized for preliminary maintenance or emergency response prior to actual on-site inspection. It is expected that such systems will not only give engineers a valuable tool in monitoring the structural performance of critical bridge systems, but will also provide important information related to durability, design criteria, and long-term response of FRP composite structures.     

基于环境振动测试的润扬桥塔模型修正

桥塔是决定大跨度桥梁结构动力特性的重要部分之一,系统而深入地认识桥塔的动力特性是十分重要的。本文采用环境激励振动测试的方法对润扬桥塔的振动特性进行了测试,识别了其重要的模态参数。为了更深入地了解桥塔的力学性质,建立了桥塔的空间结构模型,依据最小秩方法(MROU),对结构模型进行了修正,识别出桥塔中重要的力学参数。修正后的模型为进一步模拟仿真分析大型桥塔在恶劣环境下的动态响应提供基础。     

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。     

Numerical Evaluation of Vibration‐Based Methods for Damage Assessment of Cable‐Stayed Bridges

Abstract: This study investigated a number of different damage detection algorithms for structural health monitoring of a typical cable‐stayed bridge. The Bayview Bridge, a cable‐stayed bridge in Quincy, Illinois, was selected for the study. The focus was in comparing the viability of simplified techniques for practical applications. Accordingly, the numerical analysis involved development of a precise linear elastic finite element model (FEM) to simulate various structural health monitoring test scenarios with accelerometers. The Effective Independence Method was employed to locate the best distribution of the accelerometers along the length of the bridge. The simulated accelerometer data based on the FEM analysis was employed for the evaluation of the four damage identification methods investigated here. These methods included the Enhanced Coordinate Modal Assurance Criterion, Damage Index Method, Mode Shape Curvature Method, and Modal Flexibility Index Method. Some of these methods had been previously applied only to a number of specific bridges. However, the investigation here provides the relative merits and shortcomings of the damage detection methods in long‐span cable‐stayed bridges.     

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。     

Multi-scale damage analysis for a steel box girder of a long-span cable-stayed bridge

Accurate evaluation of the effect of possible damage in critical components on the dynamic characteristics of a structure is of critical importance in developing a robust structural damage identification scheme for a long-span cable-stayed bridge. The strategies of finite element (FE) modelling of a long-span cable-stayed bridge for multi-scale numerical analysis are first investigated. A multi-scale model of the Runyang cable-stayed bridge is then developed, which is essentially a multi-scale combination of a FE model for modal analysis of the entire bridge structure and FE sub-models for local stress analysis of the selected locations with respect to the substructuring method. The developed three-dimensional global-scale and local-scale FE models of Runyang cable-stayed bridge achieve a good correlation with the measured dynamic properties identified from field ambient vibration tests and stress distributions of a steel box girder measured from vehicle loading tests, on the basis of which the effectiveness of some damage location identification methods, including a modal curvature index, a modal strain energy index and a modal flexibility index, are evaluated. The analysis results show that the effect of the simulated damage in various components of the steel box girder on the dynamic characteristics of a long-span cable-stayed bridge should be properly considered in structural damage analyses using multi-scale numerical computation.