• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.667-675
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• 2012

A damage estimation method for support structure of offshore wind turbine using modal parameters is presented for effective structural health monitoring. Natural frequencies and mode shapes for a support structure with monopile of an offshore wind turbine were calculated considering soil condition and added mass. A neural network was learned based on training patterns generated by the changes of natural frequency and mode shape due to various damages. Natural frequencies and mode shapes for 10 prospective damage cases were input to the trained neural network for damage estimation. The identified damage locations and severities agreed reasonably well with the accurate damages. Multi-damage cases could also be successfully estimated. Enhancement of estimation result using another parameters as input to neural network will be carried out by further study. Proposed method could be applied to other type of support structure of offshore wind turbine for structural health monitoring.

• Journal of KIBIM
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• v.9 no.1
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• pp.42-51
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• 2019

Maintenance of aging structures has attracted societal attention. Maintenance of the aging structure can be efficiently performed with a digital twin. In order to maintain the structure based on the digital twin, it is required to accurately detect the damage of the structure. Meanwhile, deep learning-based damage detection approaches have shown good performance for detecting damage of structures. However, in order to develop such deep learning-based damage detection approaches, it is necessary to use a large number of data before and after damage, but there is a problem that the amount of data before and after the damage is unbalanced in reality. In order to solve this problem, this study proposed a method based on Generative adversarial network, one of Generative Model, for generating acceleration data usually used for damage detection approaches. As results, it is confirmed that the acceleration data generated by the GAN has a very similar pattern to the acceleration generated by the simulation with structural analysis software. These results show that not only the pattern of the macroscopic data but also the frequency domain of the acceleration data can be reproduced. Therefore, these findings show that the GAN model can analyze complex acceleration data on its own, and it is thought that this data can help training of the deep learning-based damage detection approaches.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.2
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• pp.164-172
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• 2007

Surface cracks in concrete are common defects that can cause significant deterioration and failure of concrete structures. Therefore, the early detection, assessment, and repair of the cracks in concrete are very important for the structural health. Among studies for crack depth assessment, self-calibrating surface wave transmission method seems to be a promising nondestructive technique, though it is still difficult in determination of the crack depth due to the variation of the experimentally obtained transmission functions. In this paper, the spectral energy transmission method is proposed for the crack depth estimation in concrete structures. To verify this method, an experimental study was carried out on a concrete slab with various surface-opening crack depths. Finally, effectiveness of the proposed method is validated by comparing the conventional time-of-flight and cutting frequency based methods. The results show an excellent potential as a practical and reliable in-situ nondestructive method for the crack depth estimation in concrete structures.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.6
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• pp.550-557
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• 2008

Delamination damage at a bolt hole in a composite stiffened panel was detected using a built-in piezoelectric active sensor array. Various signal processing techniques were used to detect an invisible small scale delamination around a fastener hole due to localized transverse loading. A built-in piezoelectric sensor array was used to generate diagnostic signals and to measure response signals. Then, the response signals were processed to extract damage-sensitive features. Damage indexes were calculated to estimate the severity and location of the damage from the features.

• Progress in Medical Physics
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• v.14 no.4
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• pp.259-267
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• 2003

In vivo $^1$H magnetic resonance spectroscopy (MRS) at 4.7 T was applied to investigate the cerebral metabolite changes of mice brain before and after experimental brain trauma. In vivo $^1$H MR spectra were acquired from a voxel covering right parietal cortex in normal brain, used as control subjects. After experimental brain trauma using the fluid percussion injury (FPI) method, $^1$H MR spectra were acquired from the same lesion three days after trauma. Metabolite ratios of the injured lesion were compared to those of controls. After trauma, N-acetylaspartate (NAA)/creatine (Cr) ratio, as a neuronal marker was decreased significantly versus controls, indicating neuronal loss. The ratio of NAA/Cr in traumatic brain contusion was 0.90$\pm$0.11, while that in normal control subjects was 1.13$\pm$0.12 (P=0.001). Choline (Cho)/Cr ratio had a tendency to rise in experimental brain contusion (P=0.02). Cho/Cr ratio after trauma was 0.91$\pm$0.17 while that before traumas was 0.76$\pm$0.15. Cho/Cr ratio was increased and this might indicate a inflammatory activity. However, no significant difference of [(glutamate＋glutamine) (Glx)]/Cr was established between experimental traumatic brain injury models and normal controls. Lactate (Lac)/Cr ratio was appeared as a sign of shifted posttraumatic energy metabolism and increased versus controls. These findings strongly suggest that in vivo $^1$H MRS may be a useful modality for clinical evaluation of traumatic contusion and could aid in better understanding the neuropathologic process of traumatic contusion induced by FPI. In the present study, in vivo $^1$H MRS was proved to be a useful non-invasive method for in vivo diagnosis and monitoring of posttraumatic metabolism in models of brain contusion.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.269-272
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• 2008

The seismic fragility curves of a structure represents the probability of exceeding the prescribed structural damage given various levels of ground motion intensityand the seismic fragility curve is essential to evaluation of structural performance and assessment of risk and loss of structures. The purpose of this paper is to develop seismic fragility functions for bridge structures in Koreaby reviewing those of advanced countries. Therefore, at first, we investigated development conditions of the seismic fragility functions. And the next highway bridges in Korea are classified into a number of categories and several typical bridges are selected to estimate seismic fragilities for using this analysis method in Korea. Finally, fragility curves for PSC Box girder bridge are estimated. The results show that the bridge classification and damage state play an important role in estimation of seismic damage and seismic fragility analysis for bridge structures.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.394-405
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• 2022

This paper presents the numerical estimation results of oil outflows from damaged single-hull and double-hull ships by using computational fluid dynamics (CFD) simulations. A CFD method for multi-phase flow analysis was used, and the effects of numerical parameters on oil flows was investigated. Numerical simulations were conducted to predict the changes in oil outflows under various damage conditions owing to grounding or collision accidents and verified through available experimental results. The present numerical results showed a good agreement with the experimental results according to the geometrical characteristics of single and double hulls. In particular, the oil outflows from double hulls accompanying complex interactions between water and oil were reasonably predicted a shown in the experiment. This study established a reliable CFD technique necessary for estimating the oil outflows of damaged ships.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8C
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• pp.617-626
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• 2008

Opportunistic Beamforming (OBF) offers a way to provide the multiuser diversity even in slow fading channel by using randomly generated beam weights, leading to the substantially reduced feedback in the form of the instantaneous SNR from users. In spite of the advantage of the reduced feedback, the imperfect channel estimation might influence the quality of the estimated SNR and channel scheduler so bad that the selected AMC level would be higher than the achievable rate of the actual channel, resulting the corruption of transmitted packet. In this paper, we propose a conservative link adaptation, where the estimated SNR is scaled down by a conservative factor which minimizes the variance of the maximum difference between the actual channel SNR and the resultant SNR. To support the proposed scheme, we analyze the statistics of the difference of the channel SNR and the estimated SNR. Simulation results show that the introduction of conservative factor achieves more than two-fold performance improvement in the presence of channel estimation error and the fairness of PF scheduler is maintained when the least squared channel estimator is applied.

• Composites Research
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• v.20 no.6
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• pp.21-27
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• 2007

Low-velocity impact damage in a composite stiffened panel was detected using built-in piezoelectric active sensor arrays. Using these piezoelectric active sensors, various diagnostic signals were generated to propagate Lamb waves through the structure and the responses were picked up to detect changes in the structure's vibration signature due to the damage. Three algorithms - ADI(Active Damage Interrogation), TD RMS (Time Domain Root Mean Square) and STFT (Short Time Fourier Transform) - were examined to express the features of the signal changes as one damage index. From damage detecting tests, two impact induced delaminations were detected and the location was estimated with the algorithms and diagnostic signals.

• Journal of Navigation and Port Research
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• v.32 no.3
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• pp.215-221
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• 2008

Dynamic characteristics of a structure, i.e., natural frequency and mode shape, have been widely using as an input data in the area of structural integrity or health monitoring which combined with the damage evaluation and structural system identification techniques. It is very difficult, however, to get those information by the conventional modal analysis method from large structures, such as the offshore structure or the long-span bridge, since the source of vibration is not available. In this paper, a method to obtain the frequencies and the mode shapes of a large span truss structure using only acceleration responses is studied. The calculation procedures to obtain acceleration responses and frequency response functions are provided utilizing a numerical model of the truss, and the process to extract natural frequencies and mode shapes from the modal analysis is cleary explained. The extracted mode shapes by proposed method are compared with those from eigenvalue analysis for the estimation of accuracy. The validity of the mode shapes is also demonstrated using an existing damage detection technique for the truss structure by simulated damage cases.