• Smart Structures and Systems
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• v.6 no.8
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• pp.905-920
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• 2010

Changes in temperature, loads and boundary conditions may have effects on the dynamic properties of large civil structures. Taking the Run Yang Suspension Bridge as an example, modal properties obtained from ambient vibration tests and from the structural health monitoring system of the bridge are used to identify and evaluate the modal parameter variability. Comparisons of these modal parameters reveal that several low-order modes experience a significant change in frequency from the completion of the bridge to its operation. However, the correlation analysis between measured modal parameters and the temperature shows that temperature has a slight influence on the low-order modal frequencies. Therefore, this paper focuses on the effects of the boundary conditions on the dynamic behaviors of the suspension bridge. An analytical model is proposed to perform a sensitivity analysis on modal parameters of the bridge concerning the stiffness of expansion joints located at two ends of bridge girders. It is concluded that the boundary conditions have a significant influence on the low-order modal parameters of the suspension bridge. In addition, the influence of vehicle load on modal parameters is also investigated based on the proposed model.

• Structural Engineering and Mechanics
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• v.84 no.3
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• pp.413-421
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• 2022

Modal parameters are the main dynamic characteristics of bridge. This study aims to propose an innovative route to estimate the modal parameters for bridges by using a parked vehicle in which mode shapes with high accuracy and spatial resolution are identified by frequency measurement. Based on the theory of dynamic modification and modal identification, the mathematical formulation between the parked mass induced frequency variation and the modal parameters of a bridge is derived. Then this mathematical formulation is extended to a parked vehicle-bridge system. The arithmetic and processes for estimating the modal parameters based on the identified frequency variation of the vehicle-bridge systems when the vehicle locates at sequentially arranged positions are presented. Finally the proposed method is applied to several simulated bridges of different types. The results indicate that it can estimate the modal parameters with high accuracy and efficiency.

• Smart Structures and Systems
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• v.30 no.1
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• pp.107-119
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• 2022

Modal parameters are widely used in bridge damage detection, finite element model (FEM) updating and design optimization. However, the conventional modal identification approaches require large number of sensors, enormous data processing workload, but normally result in mode shapes with low accuracy. This paper proposes a modal identification method of time-varying vehicle-bridge system using a single sensor. Firstly, the essential physical relationship between the instantaneous frequency of the vehicle-bridge system and the bridge mode shapes are derived. Subsequently, based on the synchroextracting transform, the instantaneous frequency of the system is tracked through the dynamic response collected by a single sensor, and further the modal parameters are estimated by using the derived physical relationship. Then numerical and experimental examples are conducted to examine the feasibility and effectiveness of the proposed method. Finally, the modal parameters identified by the proposed method are applied in bridge FEM updating. The results manifest that the proposed method identifies the modal parameters with high accuracy via a single sensor, and can provide reliable data for the FEM updating.

• Smart Structures and Systems
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• v.24 no.2
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• pp.243-256
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• 2019

Determination of the most meaningful structural modes and gaining insight into how these modes evolve are important issues for long-term structural health monitoring of the long-span bridges. To address this issue, modal parameters identified throughout the life of the bridge need to be compared and linked with each other, which is the process of mode tracking. The modal frequencies for a long-span bridge are typically closely-spaced, sensitive to the environment (e.g., temperature, wind, traffic, etc.), which makes the automated tracking of modal parameters a difficult process, often requiring human intervention. Machine learning methods are well-suited for uncovering complex underlying relationships between processes and thus have the potential to realize accurate and automated modal tracking. In this study, Gaussian mixture model (GMM), a popular unsupervised machine learning method, is employed to automatically determine and update baseline modal properties from the identified unlabeled modal parameters. On this foundation, a new mode tracking method is proposed for automated mode tracking for long-span bridges. Firstly, a numerical example for a three-degree-of-freedom system is employed to validate the feasibility of using GMM to automatically determine the baseline modal properties. Subsequently, the field monitoring data of a long-span bridge are utilized to illustrate the practical usage of GMM for automated determination of the baseline list. Finally, the continuously monitoring bridge acceleration data during strong typhoon events are employed to validate the reliability of proposed method in tracking the changing modal parameters. Results show that the proposed method can automatically track the modal parameters in disastrous scenarios and provide valuable references for condition assessment of the bridge structure.

• Structural Engineering and Mechanics
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• v.22 no.1
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• pp.53-70
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• 2006

The paper summarizes the dynamic-based assessment of a reinforced concrete arch bridge, dating back to the 50's. The outlined approach is based on ambient vibration testing, output-only modal identification and updating of the uncertain structural parameters of a finite element model. The Peak Picking and the Enhanced Frequency Domain Decomposition techniques were used to extract the modal parameters from ambient vibration data and a very good agreement in both identified frequencies and mode shapes has been found between the two techniques. In the theoretical study, vibration modes were determined using a 3D Finite Element model of the bridge and the information obtained from the field tests combined with a classic system identification technique provided a linear elastic updated model, accurately fitting the modal parameters of the bridge in its present condition. Hence, the use of output-only modal identification techniques and updating procedures provided a model that could be used to evaluate the overall safety of the tested bridge under the service loads.

• Smart Structures and Systems
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• v.17 no.3
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• pp.491-522
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• 2016

A benchmark problem for modal identification of a cable-stayed bridge was proposed by a research team at Hong Kong Polytechnic University. By taking an instrumented cable-stayed bridge as a test bed, nineteen sets of vibration records with known/unknown excitations were provided to invited researchers. In this paper, the vibration responses of the bridge under a series of excitation conditions are examined to estimate the wind and traffic-induced variations of its dynamic characteristics. Firstly, two output-only experimental modal identification methods are selected. Secondly, the bridge and its monitoring system are described and the nineteen sets of vibration records are analyzed in time-domain and frequency-domain. Excitations sources of blind datasets are predicted based on the analysis of excitation conditions of known datasets. Thirdly, modal parameters are extracted by using the two selected output-only modal identification methods. The identified modal parameters are examined with respect to at least two different conditions such as traffic- and typhoon-induced loadings. Finally, the typhoon-induced effects on dynamic characteristics of the bridge are estimated by analyzing the relationship between the wind velocity and the modal parameters.

• Smart Structures and Systems
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• v.31 no.1
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• pp.29-43
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• 2023

This study investigates the possibility of damage detection of a real bridge by means of a modal parameter-based finite element (FE) model update. Field moving vehicle experiments were conducted on an actual steel plate girder bridge. In the damage experiment, cracks were applied to the bridge to simulate damage states. A fast Bayesian FFT method was employed to identify and quantify uncertainties of the modal parameters then these modal parameters were used in the Bayesian model update. Material properties and boundary conditions are taken as uncertainties and updated in the model update process. Observations showed that although some differences existed in the results obtained from different model classes, the discrepancy between modal parameters of the FE model and those experimentally obtained was reduced after the model update process, and the updated parameters in the numerical model were indeed affected by the damage. The importance of boundary conditions in the model updating process is also observed. The capability of the MCMC model update method for application to the actual bridge structure is assessed, and the limitation of FE model update in damage detection of bridges using only modal parameters is observed.

• Smart Structures and Systems
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• v.20 no.2
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• pp.115-126
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• 2017

The modal identification of large civil structures such as bridges under the ambient vibrational conditions has been widely investigated during the past decade. Many operational modal analysis methods have been proposed and successfully used for identifying the dynamic characteristics of the constructed bridges in service. However, there is very limited research available on reliable criteria for the robustness of these identified modal parameters of the bridge structures. In this study, two time-domain operational modal analysis methods, the data-driven stochastic subspace identification (SSI-DATA) method and the covariance-driven stochastic subspace identification (SSI-COV) method, are employed to identify the modal parameters from field recorded ambient acceleration data. On the basis of the SSI-DATA method, the modal contribution indexes of all identified modes to the measured acceleration data are computed by using the Kalman filter, and their applicability to evaluate the robustness of identified modes is also investigated. Here, the benchmark problem, developed by Hong Kong Polytechnic University with field acceleration measurements under different excitation conditions of a cable-stayed bridge, is adopted to show the effectiveness of the proposed method. The results from the benchmark study show that the robustness of identified modes can be judged by using their modal contributions to the measured vibration data. A critical value of modal contribution index of 2% for a reliable identifiability of modal parameters is roughly suggested for the benchmark problem.

• Steel and Composite Structures
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• v.19 no.2
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• pp.385-403
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• 2015

This paper presents the status improvement of an old damaged deck type rural road steel truss bridge through the modal parametric study after partial retrofitting. The dynamic and static tests on bridge were carried out as in damaged state and after partial retrofitting. The dynamic testing on the steel bridge was carried out using accelerometers under similar environmental conditions with same speed of the moving vehicle. The comparison of the modal parameters i.e., frequency, mode shape mode shape curvature, modal strain energy, along with the deflection parameter are studied with respect to structural analytical model parameters. The status up gradation for the upper and downstream truss obtained was different due to differential level of damage in the bridge. Also after retrofitting the structural elemental behavior obtained was not same as desired. The damage level obtained through static tests carried out using total station indicated further retrofitting requirement.

• Smart Structures and Systems
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• v.19 no.6
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• pp.653-663
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• 2017

The modal parameters of the deck of Runyang Suspension Bridge (RSB) as well as their relationships with wind and temperature are studied based on the data recorded by its Structural Health Monitoring System (SHMS). Firstly, frequency analysis on the vertical responses at the two sides of the deck is carried out to distinguish the vertical and torsional vibration modes. Then, the vertical, torsional and lateral modal parameters of the deck of RSB are identified using Hilbert-Huang Transform (HHT) and validated by the identified results before RSB was opened to traffic. On the basis of this, the modal frequencies and damping ratios of RSB during the whole process of Typhoon Masta are obtained. And the correlation analysis on the modal parameters and wind environmental factors is then conducted. Results show that the HHT can achieve an accurate modal identification of RSB and the damping ratios show an obvious decay trend as the frequencies increase. Besides, compared to frequencies, the damping ratios are more sensitive to the environmental factors, in particular, the wind speed. Further study on configuring the variation law of modal parameters related with environmental factors should be continued.