• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.1150-1155
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• 2001

The updating of the FE model to match it with the experimental results needs the modal information. There are two causes where this methodology is ill-equip to deal with; under-determined and ill-conditioning problem. In this research, the feedback exciter which uses the summation of the white noise and the signals from the measurement sensors multiplied with feedback gains is proposed. The new energy path generated by the feedback exciter changes the modal characteristics of the system and this additional modal information can solve the under-determined problem in the model updating. Through the proper selection of the exciter and sensor locations and the feedback gain, the eigenvalue sensitivity of the updating parameters which cause the ill-conditioning of the sensitivity matrix can be modified. This methodology does not require any additional equipments, makes the acquirement of the additional modal information easy and is robust to the measurement noise.

• Proceedings of the KSR Conference
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• 1998.05a
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• pp.233-240
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• 1998

In the design of the high-speed railway vehicles of low noise and vibration characteristics, it is desirable to develop efficient and systematic procedures for analyzing large structures. In this paper, some finite-element modelling techniques and an efficient analytical method are proposed for this purpose. The analytical method is based on substructuring approach such as a free-interface method and a generalized synthesis algorithm. In final, the proposed approaches are applied to the finite-element modelling, modal analysis and subsequent model updating procedures of the high-speed railway intermediate trailers.

• Journal of Korean Society of Steel Construction
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• v.24 no.1
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• pp.119-128
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• 2012

In this study, experimental vibration tests are performed on a real full-scale railway steel plate girder bridge, which resides in open-space environments. Using experimental modal analysis techniques, the modal parameters of the railway steel plate girder bridge yielded by the modal testing of the impact hammer are compared and investigated with the natural frequencies and mode shapes obtained by finite element analysis. This work focuses on the application of model updating techniques to measured experimental data and output-only data from an analytical vibration study that takes into account various geometric and material properties of the bridge members. A finite element model of the railway bridge structure is used to verify the modal experimental results. It is subsequently updated using the corresponding modal identification technique. The basic database is provided to evaluate damage, which can be determined based on the changes in the element properties, resulting from the process of updating the finite element model benchmark and experimental data.

• Structural Engineering and Mechanics
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• v.46 no.5
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• pp.615-627
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• 2013

One of the most common defects in reinforced concrete bridge decks is corrosion of steel reinforcing bars. This invisible defect reduces the deck stiffness and affects the bridge's serviceability. Regular monitoring of the bridge is required to detect and control this type of damage and in turn, minimize repair costs. Because the corrosion is hidden within the deck, this type of damage cannot be easily detected by visual inspection and therefore, an alternative damage detection technique is required. This research develops a non-destructive method for detecting reinforcing bar corrosion. Experimental modal analysis, as a non-destructive testing technique, and finite element (FE) model updating are used in this method. The location and size of corrosion in the reinforcing bars is predicted by creating a finite element model of bridge deck and updating the model characteristics to match the experimental results. The practicality and applicability of the proposed method were evaluated by applying the new technique to a two spans bridge for monitoring steel bar corrosion. It was shown that the proposed method can predict the location and size of reinforcing bars corrosion with reasonable accuracy.

• Journal of Power System Engineering
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• v.4 no.2
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• pp.71-76
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• 2000

It is well known that finite element analysis often has the inaccuracy when they are in conflict with test results. Model updating is concerned with the correction of analytical model by processing records of response from test results. This paper introduce a model updating technique using the frequency response function data. The measurement data is able to be used directly in the FRF sensitivity method because it is not necessary to identify. When a damping model is updated, it is necessary for the sensitivity matrix to be divided Into the complex part and real part. As an applying model, a cantilever and a rotor system are used. Specially the machined clearance($C_p$) of the journal bearing is updated.

• Smart Structures and Systems
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• v.26 no.4
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• pp.451-468
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• 2020

Although model updating has been widely applied using a specific optimization algorithm with a single objective function using frequencies, mode shapes or frequency response functions, there are few studies that investigate hybrid optimization algorithms for real structures. Many of them did not take into account the sensitivity of the updating parameters to the model outputs. Therefore, in this paper, optimization algorithms and sensitivity analysis are applied for model updating of a real cable-stayed bridge, i.e., the Kien bridge in Vietnam, based on experimental data. First, a global sensitivity analysis using Morris method is employed to find out the most sensitive parameters among twenty surveyed parameters based on the outputs of a Finite Element (FE) model. Then, an objective function related to the differences between frequencies, and mode shapes by means of MAC, COMAC and eCOMAC indices, is introduced. Three metaheuristic algorithms, namely Gravitational Search Algorithm (GSA), Particle Swarm Optimization algorithm (PSO) and hybrid PSOGSA algorithm, are applied to minimize the difference between simulation and experimental results. A laboratory pipe and Kien bridge are used to validate the proposed approach. Efficiency and reliability of the proposed algorithms are investigated by comparing their convergence rate, computational time, errors in frequencies and mode shapes with experimental data. From the results, PSO and PSOGSA show good performance and are suitable for complex and time-consuming analysis such as model updating of a real cable-stayed bridge. Meanwhile, GSA shows a slow convergence for the same number of population and iterations as PSO and PSOGSA.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.5
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• pp.107-115
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• 2008

In this paper, we have proposed a wear growth prediction method on the surface of rubber pad of track assembly installed in high-speed battle tank i.e. the automatic model updating code interfacing with commercial finite element simulation software. Also, simple and resonable geometrical, material finite element model was established to be easily updated based on the empirical threshold value of contact pressure on the contact surface. From the iterative model update and analysis results, we discovered a weak point on rubber pad surface and suggested a new design concept for improving the wear performance of track assembly.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.5
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• pp.445-452
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• 2009

In this paper, damage detection procedure using the finite element model updating was formulated and applied to a small-scale frame structure. FE model updating is the analytical method which finds the mathematical model that generates the measured dynamic properties similarly, and can be effectively used for the damage detection and SHM. For model updating, several kinds of dynamic properties, such as the natural frequencies, mode shapes, and frequency response functions, can be used as the inputs. In this paper, two kinds of model updating procedures using the natrual frequency and the frequency response function, and the natrual frequency and the mode shapes, respectively, were applied to identify the location and the severity of damage of the test structure, which is a four-story two bay steel structure. Results from the damage detection showed that more accurate identification results was obtained when the natrual frequency and the frequency response function were used than when the natrual frequency and the mode shapes were used.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.9
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• pp.884-891
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• 2009

This study investigates some of swarm intelligence algorithms to tackle a traditional damage detection problem having stiffness degradation or damage in mechanical structures. Particle swarm(PSO) and ant colony optimization(ACO) methods have been exploited for localizing and estimating the location and extent damages in a structure. Both PSO and ACO are population-based, stochastic algorithms that have been developed from the underlying concept of swarm intelligence and search heuristic. A finite element (FE) model updating is implemented to minimize the difference in a set of natural frequencies between measured and baseline vibration data. Stiffness loss of certain elements is considered to simulate structural damages in the FE model. It is numerically shown that PSO and ACO algorithms successfully completed the optimization process of model updating in locating unknown damages in a truss structure.

• Structural Monitoring and Maintenance
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• v.7 no.3
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• pp.261-281
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• 2020

Civil structures may experience progressive deterioration and damage under environmental and operational conditions over their service life. Finite element (FE) model updating method is one of the most important approaches for damage identification in structures due to its capabilities in structural health monitoring. Although various damage detection approaches have been investigated on structures, there are limited studies on large-sized space structures. Thus, this paper aims to investigate the applicability and efficiency of sensitivity-based FE model updating framework for damage identification in large space structures from a distinct point of view. This framework facilitates modeling and model updating in large and geometric complicated space structures. Considering sensitivity-based FE model updating and vibration measurements, the discrepancy between acceleration response data in real damaged structure and hypothetical damaged structure have been minimized through adjusting the updating parameters. The feasibility and efficiency of the above-mentioned approach for damage identification has finally been demonstrated with two numerical examples: a flat double layer grid and a double layer diamatic dome. According to the results, this method can detect, localize, and quantify damages in large-scaled space structures very accurately which is robust to noisy data. Also, requiring a remarkably small number of iterations to converge, typically less than four, demonstrates the computational efficiency of this method.