• 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.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.6
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• pp.579-592
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• 2010

This paper presents a multi-phase model update approach for system identification of prestressed concrete (PSC) girders under various prestress forces. First, a multi-phase model update approach designed on the basis of eigenvalue sensitivity concept is newly proposed. Next, the proposed multi-phase approach is evaluated from controlled experiments on a lab-scale PSC girder for which forced vibration tests are performed for a series of prestress forces. On the PSC girder, a few natural frequencies and mode shapes are experimentally measured for the various prestress forces. The corresponding modal parameters are numerically calculated from a three-dimensional finite element (FE) model which is established for the target PSC girder. Eigenvalue sensitivities are analyzed for potential model-updating parameters of the FE model. Then, structural subsystems are identified phase-by-phase using the proposed model update procedure. Based on model update results, the relationship between prestress forces and model-updating parameters is analyzed to evaluate the influence of prestress forces on structural subsystems.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.425-428
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• 2009

This paper presents a sensitivity-based finite element (FE)-model update procedure for prestressed concrete (PSC) girder bridge model using vibration test results. Firstly, the stiffness parameters of the structure such as flexural rigidity of concrete and flexural rigidity of tendon are chosen as updating parameters. Next, the numerical frequencies of first two bending modes are calculated using a three-dimensional FE model which is established for the PSC girder. Then, the corresponding experimental frequencies which are obtained from forced vibration tests are selected. In order to perform the model update, the eigensensitivity-based method is employed. Finally, the effect of prestress-loss on the stiffness parameters is evaluated.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.12
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• pp.830-842
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• 2015

This paper aims to develop a SI(structural identification) technique using the kinetic energy optimization technique(KEOT) and the direct matrix updating method(DMUM) to decide on optimal location of sensors and to update FE model respectively, which ultimately contributes to a composition of more effective SHM. Owing to the characteristic structural flexing behavior of cable bridges, which makes them vulnerable to any vibration, systematic and continuous structural health monitoring (SHM) is pivotal for them. Since it is necessary to select optimal measurement locations with the fewest possible measurements and also to accurately assess the structural state of a bridge for the development of an effective SHM, a SI technique is as much important to accurately determine the modal parameters of the current structure based on the data optimally obtained. In this study, the KEOT was utilized to determine the optimal measurement locations, while the DMUM was utilized for FE model updating. As a result of experiment, the required number of measurement locations derived from KEOT based on the target mode was reduced by approximately 80 % compared to the initial number of measurement locations. Moreover, compared to the eigenvalue of the modal experiment, an improved FE model with a margin of error of less than 1 % was derived from DMUM. Finally, the SI technique for long-span bridges proposed in this study, which utilizes both KEOT and DMUM, is proven effective in minimizing the number of sensors while accurately determining the structural dynamic characteristics.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.471-483
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• 2012

In this paper, the structural health monitoring (SHM) benchmark problem of the Canton tower is studied. Based on the field monitoring data from the 20 accelerometers deployed on the tower, some modal frequencies and mode shapes at measured degrees of freedom of the tower are identified. Then, these identified incomplete modal data are used to update the reduced finite element (FE) model of the tower by a novel algorithm. The proposed algorithm avoids the problem of subjective selection of updated parameters and directly updates model stiffness matrix without model reduction or modal expansion approach. Only the eigenvalues and eigenvectors of the normal finite element models corresponding to the measured modes are needed in the computation procedures. The updated model not only possesses the measured modal frequencies and mode shapes but also preserves the modal frequencies and modes shapes in their normal values for the unobserved modes. Updating results including the natural frequencies and mode shapes are compared with the experimental ones to evaluate the proposed algorithm. Also, dynamic responses estimated from the updated FE model using remote senor locations are compared with the measurement ones to validate the convergence of the updated model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.68-73
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• 2002

It is necessary first to understand dynamic characteristics of bus full BIW assembly for fatigue endurance analysis. FE model has been used usually for analyzing the dynamic behavior of structures. A lot of experience and effort, however, is necessary to make the credible FE model. Experimental modal analysis of structures has been performed to verify the credibility of initial FE model and to update the model. In this work, experimental modal analysis was performed to understand dynamic characteristics of bus full BIW assembly in free-free boundary condition and the result was used to verify the initial FE model. In addition, some practical techniques, which were used in this experiment, were mentioned.

• Structural Engineering and Mechanics
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• v.32 no.5
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• pp.667-683
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• 2009

FE model-based dynamic analysis has been widely used to predict the dynamic characteristics of civil structures. In a physical point of view, an FE model is unavoidably different from the actual structure as being formulated based on extremely idealized engineering drawings and design data. The conventional model updating methods such as direct method and sensitivity-based parameter estimation are not flexible for model updating of complex and large structures. Thus, it is needed to develop a model updating method applicable to complex structures without restriction. The main objective of this paper is to present the model updating method based on the hybrid genetic algorithm (HGA) by combining the genetic algorithm as global optimization method and modified Nelder-Mead's Simplex method as local optimization method. This FE model updating method using HGA does not need the derivation of derivative function related to parameters and without application of complicated inverse analysis methods. In order to allow its application on diversified and complex structures, a commercial FEA tool is adopted to exploit previously developed element library and analysis algorithms. Moreover, an output-level objective function making use of measurement and analytical results is also presented to update simultaneously the stiffness and mass of the analysis model. The numerical examples demonstrated that the proposed method based on HGA is effective for the updating of the FE model of bridge structures.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.52.3-52
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• 2002

Natural frequencies and mode shapes are two important modal data which specify the system. If the real system and FE model don't have the same local physical parameters, there will be a difference between modal data from real system and FE model. Because there is little difference in displacement mode shapes measured by an accelerometer, displacement modal update based on mode shapes including measurement errors may not be successful. In this research, strain mode shapes are used as modal data because the strain mode shapes measured by strain gauges are more sensitive than the displacement mode shapes with respect to the change of the parameters concerned in FE stiffness matrix...

• Smart Structures and Systems
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• v.15 no.3
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• pp.751-767
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• 2015

A new procedure is proposed for assessing probabilistic condition of structures considering effect of measured data uncertainty. In this procedure, multiple Finite Element (FE) models are identified by using weighting vectors that represent the uncertainty conditions of measured data. The distribution of structural parameters is analysed using a Principal Component Analysis (PCA) in relation to uncertainty conditions, and the identified models are classified into groups according to their similarity by using a K-means method. The condition of a structure is then assessed probabilistically using FE models in the classified groups, each of which represents specific uncertainty condition of measured data. Yeondae bridge, a steel-box girder expressway bridge in Korea, is used as an illustrative example. Probabilistic condition of the bridge is evaluated by the distribution of load rating factors obtained using multiple FE models. The numerical example shows that the proposed method can quantify uncertainty of measured data and subsequently evaluate efficiently the probabilistic condition of bridges.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.195-204
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• 2000

The finite element analysis (FEA) is widely used in modern structural dynamics because the performance of structure can be predicted in early stage. However, due to the difficulty in determination of various uncertain parameters, it is not easy to obtain a reliable finite element model. To overcome these difficulties, a updating program of FE model is developed by consisting of pretest, correlation and update. In correlation, it calculates modal assurance criteria, cross orthogonality, mixed orthogonality and coordinate modal assurance criteria. For the model updating, the continuum sensitivity analysis and design optimization tool(DOT) are used. The SENSUP program is developed for model updating giving physical parameter sensitivity. The developed program is applied to practical examples such as the BLDC spindle motor of HDD, and upper housing of induction motor. And the sensor placement for the square plate is compared using several methods.