• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.625-628
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• 1997

In this paper the new neural network and sliding mode suspension controller is proposed. That neural network is error self-recurrent neural network. For fast on-line learning, this paper use recursive least squares method. A new neural networks converges considerably faster than the backpropagation algorithm and has advantages of being less affected by the poor initial weights and learning rate. The controller for suspension systems is designed according to sliding mode technique based on new proposed neural network.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.799-808
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• 2017

Failure of a redundant long-span bridge is often described by innumerable failure modes, which make the structural system reliability analysis become a computationally intractable work. In this paper, an innovative procedure is proposed to efficiently identify the dominant failure modes and quantify the structural reliability for a long-span bridge system. The procedure is programmed by ANSYS and MATLAB. Considering the correlation between failure paths, a new branch and bound operation criteria is applied to the traditional stage critical strength branch and bound algorithm. Computational effort can be saved by ignoring the redundant failure paths as early as possible. The reliability of dominant failure mode is computed by FORM, since the limit state function of failure mode can be expressed by the final stage critical strength. PNET method and FORM for system are suggested to be the suitable calculation method for the bridge system reliability. By applying the procedure to a CFST arch bridge, the proposed method is demonstrated suitable to the system reliability analysis for long-span bridge structure.

• Structural Monitoring and Maintenance
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• v.5 no.3
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• pp.379-390
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• 2018

In this paper, a novel and effective damage diagnosis algorithm is proposed to detect and estimate damage using two stages least squares support vector machine (LS-SVM) and limited number of attached sensors on structures. In the first stage, LS-SVM1 is used to predict the unmeasured mode shapes data based on limited measured modal data and in the second stage, LS-SVM2 is used to predicting the damage location and severity using the complete modal data from the first-stage LS-SVM1. The presented methods are applied to a three story irregular frame and cantilever plate. To investigate the noise effects and modeling errors, two uncertainty levels have been considered. Moreover, the performance of the proposed methods has been verified through using experimental modal data of a mass-stiffness system. The obtained damage identification results show the suitable performance of the proposed damage identification method for structures in spite of different uncertainty levels.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.328-334
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• 2001

Up to now. vibration analysis and vibration engineering have been developed, encompassing the aspects of both experimental and analytical techniques. Using experimental modal analysis or modal testing, the mode shapes and frequencies of practical structure can be measured accurately. Curve-Fitting Method is realized through experimental modal identification. In the experimental modal parameter estimation, the estimation of modal damping factor is difficult for complicated and large structure. Also numbers of Selected mode are determined before the procedure. This paper describes the vibration shape of the super-structure model of ship through experimental modal analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.665-668
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• 2008

The load distribution to each mode of a structure under seismic loading depends on the modal participation factor. The factor of an idealized analytical model, however, is different to the actual one due to modeling and construction error. Therefore, there exist limits on the estimation of actual behavior. In this study, an identification procedure for participation factor based on vibration test is proposed. The procedure has an advantage that the mode shape vector can also be estimated directly from the participation factor. The numerical simulation using a three story building is performed to evaluate the proposed procedure.

• YAKHAK HOEJI
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• v.55 no.4
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• pp.289-294
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• 2011

Illegal addition of steroids into cosmetics, ointments or drugs have been increased and their careless usage induced detrimental effect on health. We developed simultaneous analytical method using TLC, HPLC and LC/MS for the identification of 40 corticosteroids. 34 corticosteroids were well separated in HPLC with isocratic mode and remaining 6 drugs were also separated with gradient mode. All of the 40 corticosteroids were detected in negative mode in LC/MS. Halcinonide, prednisolone, triamcinolone acetonide and methylprednisolone hemisuccinate were detected in real samples.

• Wind and Structures
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• v.9 no.6
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• pp.441-455
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• 2006

A more applicable optimization model for extracting flutter derivatives of bridge decks is presented, which is suitable for time-varying weights for fitting errors and different lengths of vertical bending and torsional free vibration data. A stochastic search technique for searching the optimal solution of optimization problem is developed, which is more convenient in understanding and programming than the alternate iteration technique, and testified to be a valid and efficient method using two numerical examples. On the basis of the section model test of Sutong Bridge deck, the flutter derivatives are extracted by the stochastic search technique, and compared with the identification results using the modified least-square method. The Empirical Mode Decomposition method is employed to eliminate noise, trends and zero excursion of the collected free vibration data of vertical bending and torsional motion, by which the identification precision of flutter derivatives is improved.

• ETRI Journal
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• v.31 no.4
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• pp.376-386
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• 2009

An active radio frequency identification (RFID) system has the advantages of a long identification distance and a good identification rate, overcoming passive RFID drawbacks. Therefore, interest in the development of active RFID systems has been gradually increasing in areas of harbor logistics and national defense. However, some identification failures between active RFID systems developed under the same standards have been reported, presumably due to a lack of development of accurate evaluation methods and test equipment. We present a realization of the hardware and software of an emulator to evaluate the standard conformance of an active RFID system in a fully anechoic chamber. The performance levels of the designed emulator are analyzed using Matlab/Simulink simulations, and the applicability of the emulator is verified by evaluating the standard conformance of a real active RFID tag. Finally, we propose a new evaluation method by incorporating a self-running test mode environment into the RFID tags to reduce testing time and increase testing accuracy. The application of the suggested method to actual tags improves measurement uncertainty by 0.56 dB over that obtained using existing methods.

• Smart Structures and Systems
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• v.25 no.3
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• pp.345-368
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• 2020

The present work proposes a self-controlled multi-stage optimization method for damage identification of structures utilizing standard particle swarm optimization (PSO) algorithm. Damage identification problem is formulated as an inverse optimization problem where damage severity in each element of the structure is considered as optimization variables. An efficient objective function is formed using the first few frequencies and mode shapes of the structure. This objective function is minimized by a self-controlled multi-stage strategy to identify and quantify the damage extent of the structural members. In the first stage, standard PSO is utilized to get an initial solution to the problem. Subsequently, the algorithm identifies the most damage-prone elements of the structure using an adaptable threshold value of damage severity. These identified elements are included in the search space of the standard PSO at the next stage. Thus, the algorithm reduces the dimension of the search space and subsequently increases the accuracy of damage prediction with a considerable reduction in computational cost. The efficiency of the proposed method is investigated and compared with available results through three numerical examples considering both with and without noise. The obtained results demonstrate the accuracy of the present method can accurately estimate the location and severity of multi-damage cases in the structural systems with less computational cost.