• Smart Structures and Systems
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• v.6 no.5_6
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• pp.461-480
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• 2010

This paper analyses the data collected from the $2^{nd}$ Jindo Bridge, a cable-stayed bridge in Korea that is a structural health monitoring (SHM) international test bed for advanced wireless smart sensors network (WSSN) technology. The SHM system consists of a total of 70 wireless smart sensor nodes deployed underneath of the deck, on the pylons, and on the cables to capture the vibration of the bridge excited by traffic and environmental loadings. Analysis of the data is performed in both the time and frequency domains. Modal properties of the bridge are identified using the frequency domain decomposition and the stochastic subspace identification methods based on the output-only measurements, and the results are compared with those obtained from a detailed finite element model. Tension forces for the 10 instrumented stay cables are also estimated from the ambient acceleration data and compared both with those from the initial design and with those obtained during two previous regular inspections. The results of the data analyses demonstrate that the WSSN-based SHM system performs effectively for this cable-stayed bridge, giving direct access to the physical status of the bridge.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.35-42
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• 2021

This paper presents an on-line finite element model updating method for in-service structures using measured data. Conventional updating methods, which are based on numerical optimization, are not efficient for on-line updating because they generally require repeated eigenvalue analyses until convergence criteria are met. The proposed method enables fully automated on-line finite element model updating, almost simultaneously with vibration measurement, without any user intervention or off-line procedures. The automated covariance-driven stochastic subspace identification (Cov-SSI) method is utilized to identify modal frequencies and vectors, and the identified modal data is fed to the neural network of the inverse eigenvalue function to produce the updated finite element model parameters. Numerical examples for a wind excited 20-story building structure shows that the proposed method can update the series of finite element model parameters automatically. It is also shown that sudden changes in the structural parameters can be detected and traced successfully.

• Tribology and Lubricants
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• v.40 no.1
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• pp.28-37
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• 2024

This paper presents the development of a squeeze film damper (SFD) test rig and experimental identification of the effects of clearance, damper length, journal eccentricity ratio, excitation amplitude, oil supply pressure, and oil flow rate on the damping coefficients of a test SFD with open ends and a central groove. Test data are compared with predictions from a simple model developed for short SFDs with open ends and a central groove. The test results show a significant decrease in the damping coefficient with increasing clearance and a dramatic increase with damper length, which are in good agreement with the simple model predictions. According to the simple model, the damping coefficient is inversely proportional to the cube of the clearance and directly proportional to the cube of the length. An increase in the journal eccentricity ratio results in a dramatic increase in the damping coefficient by as much as 15 times that of the concentric case, particularly at low excitation frequencies. By contrast, the measured damping coefficient remains almost constant with changes in the excitation amplitude and supply pressure, which are not major factors in the damper design. In general, the test data agree well with the simple model predictions, excluding cases that show increases in the SFD length and journal eccentricity, which indicate significant dependency on the excitation frequency.

• Smart Structures and Systems
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• v.33 no.2
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• pp.165-175
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• 2024

Rotating beams play a crucial role in representing complex mechanical components that are prevalent in vital sectors like energy and transportation industries. These components are susceptible to the initiation and propagation of cracks, posing a substantial risk to their structural integrity. This study presents a two-stage methodology for detecting the location and estimating the size of an open-edge transverse crack in a rotating Euler-Bernoulli beam with a uniform cross-section. Understanding the dynamic behavior of beams is vital for the effective design and evaluation of their operational performance. In this regard, modal parameters such as natural frequencies and eigenmodes are frequently employed to detect and identify damages in mechanical components. In this instance, the Frobenius method has been employed to determine the first two natural frequencies and corresponding eigenmodes associated with flapwise bending vibration. These calculations have been performed by solving the governing differential equation that describes the motion of the beam. Various parameters have been considered, such as rotational speed, beam slenderness, hub radius, and crack size and location. The effect of the crack has been replaced by a rotational spring whose stiffness represents the increase in local flexibility as a result of the damage presence. In the initial phase of the proposed methodology, a damage index utilizing the slope of the beam's eigenmode has been employed to estimate the location of the crack. After detecting the presence of damage, the size of the crack is determined using a Genetic Algorithm optimization technique. The ultimate goal of the proposed methodology is to enable the development of more suitable and reliable maintenance plans.

• Journal of the Earthquake Engineering Society of Korea
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• v.1 no.1
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• pp.41-49
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• 1997

This paper presents the result of an international cooperative research on the post-correlation analysis of forced vibration tests and the prediction of earthquake responses of a large-scale seismic test structure. The dynamic analysis is carried out using the axisymmetric finite element method incorporating in finite elements for the for field soil region. Through the post-correlation analysis, the properties of the soil layers are revised so that the best correlation in the responses may be obtained compared with the measured force vibration test data. Utilizing the revised soil properties as the initial linear values, the seismic responses are predicted for an earthquake using the equivalent linearlization technique. It has been found that the predicted responses by the equivalent nonlinear procedure are in excellent agreement with the observed responses, while those using the linear properties are fairly off from the measured results.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.9
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• pp.781-788
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• 2013

Grunt(stick-slip) noise happens between rear lining and drum on braking condition while vehicle is returning to steady position after nose-dive. The study presents a new testing and analysis methods for improving brake grunt noise on vehicle. Grunt noise is called a kind of stick slip noise with below 1 kHz frequency that is caused by the surfaces alternating between sticking to each other and sliding over each other with a corresponding change in friction force. This noise is typically come from that the static friction coefficient of surfaces is much higher than the kinetic friction coefficient. For the identification of the excitation mechanism and improvement of grunt noise, it is necessary to study variable parameters of rear drum brake systems on vehicle and to implement CAE analysis with stick slip model of drum brake. The aim of this study has been to find solution parameters throughout test result on vehicle and dynamo test. As a result of this study, it is generated from stick slip between rear lining and rear drum and it can be solved to reduce contact angle of lining with asymmetric and is effected not only brake drum strength but also rear brake size and brake factor.

• Journal of Korean Association for Spatial Structures
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• v.20 no.2
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• pp.51-58
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• 2020

Recently, deep learning that is the most popular and effective class of machine learning algorithms is widely applied to various industrial areas. A number of research on various topics about structural engineering was performed by using artificial neural networks, such as structural design optimization, vibration control and system identification etc. When nonlinear semi-active structural control devices are applied to building structure, a lot of computational effort is required to predict dynamic structural responses of finite element method (FEM) model for development of control algorithm. To solve this problem, an artificial neural network model was developed in this study. Among various deep learning algorithms, a recurrent neural network (RNN) was used to make the time history response prediction model. An RNN can retain state from one iteration to the next by using its own output as input for the next step. An eleven-story building structure with semi-active tuned mass damper (TMD) was used as an example structure. The semi-active TMD was composed of magnetorheological damper. Five historical earthquakes and five artificial ground motions were used as ground excitations for training of an RNN model. Another artificial ground motion that was not used for training was used for verification of the developed RNN model. Parametric studies on various hyper-parameters including number of hidden layers, sequence length, number of LSTM cells, etc. After appropriate training iteration of the RNN model with proper hyper-parameters, the RNN model for prediction of seismic responses of the building structure with semi-active TMD was developed. The developed RNN model can effectively provide very accurate seismic responses compared to the FEM model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.124-127
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• 2005

As computer capability and test skill become more and more advanced, finite element method and modal test are being widely applied in engineering design. In order to correlate and reconcile the inevitable discrepancies between the analytical and experimental models, many techniques have been developed. Among these methods, multiple-system methods are known as the effective tools in that they can supply the rich modal data available which are experimentally obtained. These abundant modal data can help structural system parameters estimated well. Multiple-system methods can be classified into the structural modification methods and feedback controller methods. The structural modification methods need the physical attachment of structures and their concept may limit the application of them. To overcome this drawback, the feedback controller methods are addressed which enable us to get more modal data without the structural change. Mode decoupling controller(MDC), one of them, is to use acceleration out)ut feedback to perturb an open-loop system. The output feedback controller generally cannot guarantee the stability of a closed-loop system. However, MDC can solve this problem under the certain constraints. So far, MDC utilizes accelerations as the sensor signals. In this research, strain sensors are going to be picked up to apply to the MDC. Strain output is recently used for structural system identification due to the drastically improved and miniaturized strain sensor. In this paper, we show that the MDC using strain output has differences compared with acceleration output in estimating the structural system parameters. The associated simulation is performed to demonstrate the above mentioned characteristics.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.381-387
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• 2002

In this work, the dynamic characteristics of an oil-lubricated, short SFD with a central feeding groove are derived based on a theoretical analysis considering the effect of a groove. The validity of the analysis is investigated experimentally using an Active Magnetic Bearing (AMB) system as an exciter. For the theoretical solution, the fluid film forces of a grooved SFD are analytically derived so that the dynamic coefficients of a SFD are expressed in terms of its design parameters. For the experimental validation of the analysis, a test rig using AMB as an exciter is proposed to identify the dynamic characteristics of a short SFD with a central groove. As an exciter, the AMB represents a mechatronic device to levitate and position the test journal without any mechanical contact, to generate relative motions of the journal inside the tested SFD and to measure the generated displacements during experiments with fairly high accuracy. Using this test rig, experiments are extensively conducted with different clearance, which is one of the most important design parameters, in order to investigate its effect on the dynamic characteristics and the performance of SFDs. Damping and inertia coefficients of the SFD that are experimentally identified are compared with the analytical results to demonstrate the effectiveness of the analysis. It is also shown that AMB is an ideal device for tests of SFDs.