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

• Smart Structures and Systems
• /
• v.17 no.2
• /
• pp.209-230
• /
• 2016

The Canton Tower is a high-rise slender structure with a height of 610 m. A structural health monitoring system has been instrumented on the structure, by which data is continuously monitored. This paper presents an investigation on the identified modal properties of the Canton Tower using ambient vibration data collected during a whole day (24 hours). A recently developed Fast Bayesian FFT method is utilized for operational modal analysis on the basis of the measured acceleration data. The approach views modal identification as an inference problem where probability is used as a measure for the relative plausibility of outcomes given a model of the structure and measured data. Focusing on the first several modes, the modal properties of this supertall slender structure are identified on non-overlapping time windows during the whole day under normal wind speed. With the identified modal parameters and the associated posterior uncertainty, the distribution of the modal parameters in the future is predicted and assessed. By defining the modal root-mean-square value in terms of the power spectral density of modal force identified, the identified natural frequencies and damping ratios versus the vibration amplitude are investigated with the associated posterior uncertainty considered. Meanwhile, the correlations between modal parameters and temperature, modal parameters and wind speed are studied. For comparison purpose, the frequency domain decomposition (FDD) method is also utilized to identify the modal parameters. The identified results obtained by the Bayesian method, the FDD method and a finite element model are compared and discussed.

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

• Journal of the korean Society of Automotive Engineers
• /
• v.14 no.1
• /
• pp.25-37
• /
• 1992

Interior noise in a car is known to have an important influence on product acceptability. This noise is closely correlated with structural-acoustic vibration. When considering noise problem, the structural-acoustic relation of a vehicle cabin model needs to be identified. However, it is very difficult to get the modal parameters of this kind of cabin structure composed of thin plates: because it not only can be excited by the acoustic vibration of cavity, but also tends to have decoupling effects of one plate from another. In order to obtain modal parameters more precisely, various excitation techniques, i.e. impact, pure random, burst random, and swept sine testing are applied for the first step. In the case of the cabin model, impact and swept sine testing show good results. Next, the determination of the excitation point by trial- and-error and the accurate measurements of FRF's are performed with these methods. The modal parameter extraction is carried out for the final step. This paper proposes a new approach to find the modal parameters more reliably in the case of high decoupling effects. That is, the convergence of MIF and MCF in each panel, which provide some criteria for the validity of the obtained modal parameters, is observed. And from those results, the pretty accurate modal parameters can be determined. A comparative assessment between the modal testing and the FEM is also performed.

• Smart Structures and Systems
• /
• v.30 no.1
• /
• pp.107-119
• /
• 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
• /
• v.20 no.2
• /
• pp.115-126
• /
• 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.

• Journal of Industrial Technology
• /
• v.29 no.A
• /
• pp.19-25
• /
• 2009

The proper orthogonal decomposition (POD) analysis of vibration of a steel frame structure is performed to extract modal parameters. The theoretical background of the POD method is introduced briefly, and this technique is further applied to free vibration displacements of one bay-two story steel frame structure to extract the modal parameters. From the POD analysis of the steel frame structure, it is found that important modal parameters such as true mode shapes, modal kinematic energy, natural frequencies, and damping ratios can be obtained for the building efficiently and in detail. Therefore, it is concluded that the POD method could be one of the useful techniques in analysis of vibration of structures.

• International Journal of Aeronautical and Space Sciences
• /
• v.17 no.2
• /
• pp.184-194
• /
• 2016

In existing identification methods for on-orbit spacecraft, such as eigensystem realization algorithm (ERA) and subspace method identification (SMI), singular value decomposition (SVD) is used frequently to estimate the modal parameters. However, these identification methods are often used to process the linear time-invariant system, and there is a lower computation efficiency using the SVD when the system order of spacecraft is high. In this study, to improve the computational efficiency in identifying time-varying modal parameters of large spacecraft, a faster recursive algorithm called fast approximated power iteration (FAPI) is employed. This approach avoids the SVD and can be provided as an alternative spacecraft identification method, and the latest modal parameters obtained can be applied for updating the controller parameters timely (e.g. the self-adaptive control problem). In numerical simulations, two large flexible spacecraft models, the Engineering Test Satellite-VIII (ETS-VIII) and Soil Moisture Active/Passive (SMAP) satellite, are established. The identification results show that this recursive algorithm can obtain the time-varying modal parameters, and the computation time is reduced significantly.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1997.04a
• /
• pp.97-105
• /
• 1997

A methodology to identify a baseline modal model of a complicated 3-D structure using limited structural and modal information is experimentally examined. In the first part, a system's identification theory for the methodology to identify, baseline modal responses of the structure is outlined. Next, an algorithm is designed to build a generic finite element model of the baseline structure and to calibrate the model by using only a set of post-damage modal parameters. In the second part, the feasibility of the methodology is examined experimentally using a field-tested truss bridge far which only post-damaged modal responses were measured for a few vibration modes. For the complex 3-D bridge with many members, we analyzed to identify unknown stiffness parameters of the structure by using modal parameters of the initial two modes of vibration.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.3 no.2
• /
• pp.147-154
• /
• 1999

A new approach to conducting the vibration parameters identification algorithm is proposed. The approach employs the concept of modal amplitude ratio implemented in a mode shape estimation. The accuracy of the improved Ibrahim Time Domain identification algorithm in extracting structural modal parameters from free response functions has been studied using computer simulated data for 9 stations on the two-span continuous beam. Simulated responses from the lumped and distributed parameter system demonstrate that this algorithm produces excellent results, even in the 300% noise response.