• 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.

• Journal of Korean Association for Spatial Structures
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• v.17 no.3
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• pp.4-8
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• 2017

• Composites Research
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• v.31 no.4
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• pp.145-150
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• 2018

Various structural health monitoring (SHM) systems have been suggested for aerospace industry in order to increase its life-cycle and economic efficiency. In the case of aircraft structure madden with metal, a major concern was hot spots, such as notches, bolts holes, and where corrosion or stress concentration occurs due to moisture or salinity. However, with the increasing use of composites in the aerospace industry, further advanced SHM systems have been being required to be applied to composite structures, which have much complex damage mechanism. In this paper, a method of acoustic emission localization for composite structures using Q-switched laser and multiple Amplifier-integrated PZTs have been proposed. The presented technique aims at localization of the AE with an error in distance of less than 10 mm. Acoustic emission simulation and the localization attempt were conducted in the composite structure to validate the suggested method. Localization results, which are coordinates of detected regions, grid plots and color intensity map have been presented together to show reliability of the method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.233-242
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• 2023

The unscented Kalman filter (UKF), which is widely used to estimate the states of nonlinear dynamic systems, can be improved to realize robust system identification by using multiple sigma-point sets. When using Kalman filter methods for system identification, artificial noises must be appropriately selected to achieve optimal estimation performance. Additionally, an appropriate scaling factor for the sigma-points must be selected to capture the nonlinearity of the state-space model. This study entailed the use of Bouc-Wen hysteresis model to examine the nonlinear behavior of a single-degree-of-freedom oscillator. On the basis of the effects of the selected artificial noises and scaling factor, a new UKF method using multiple sigma-point sets was devised for improved robustness of the estimation over various signal-to-noise-ratio values. The results demonstrate that the proposed method can accurately track nonlinear system states even when the measurement noise levels are high, while being robust to the selection of artificial noise levels.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.175-181
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• 2022

The condition of infrastructure deteriorates as the service life increases. Since most infrastructure in South Korea were intensively built during the period of economic growth, the proportion of outdated infrastructure is rapidly increasing now. Aging of such infrastructure can lead to safety accidents and even human casualties. To prevent these issues in advance, periodic and accurate inspection is essential. For this reason, the need for research to detect various types of damage using computer vision and deep learning is increasingly required in the field of remotely controlled or autonomous inspection. To this end, this study proposed a neural network structure that can detect concrete damage by classifying it into three types. In particular, the proposed neural network can detect them more accurately through a hierarchical learning technique. This neural network was trained with 2,026 damage images and tested with 508 damage images. As a result, we completed an algorithm with average mean intersection over union of 67.04% and F1 score of 52.65%. It is expected that the proposed damage detection algorithm could apply to accurate facility condition diagnosis in the near future.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.5
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• pp.443-451
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• 2013

Acoustic emission(AE) has emerged as a powerful nondestructive tool to detect any further growth or expansion of preexisting defects or to characterize failure mechanisms. Recently, this kind of technique, that is an in-situ monitoring of inside damages of materials or structures, becomes increasingly popular for monitoring the integrity of large structures like a huge wind turbine blade. In this study, the activities of AE signals generated from external artificial sources was evaluated and located by new developed signal mapping source location method and this test is conducted by 750 kW full-scale blade. And a new source location method was applied to assess the damage in the wind turbine blade during step-by-step static load test. In this static loading test, we have used a full scale blade of 100 kW in capacity. The results show that the acoustic emission activities give a good agreement with the stress distribution and damage location in the blade. Finally, the applicability of the new source location method was confirmed by comparison of the result of source location and experimental damage location.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.49-56
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• 2023

This study proposed a damage location estimation method for automated image-based port infrastructure inspection. Memory efficiency was improved by calculating the homography matrix using feature detection technology and outlier removal technology, without going through the 3D modeling process and storing only damage information. To develop an algorithm specialized for port infrastructure, the algorithm was optimized through ground-truth coordinate pairs created using images of port infrastructure. The location errors obtained by applying this to the sample and concrete wall were (X: 6.5cm, Y: 1.3cm) and (X: 12.7cm, Y: 6.4cm), respectively. In addition, by applying the algorithm to the concrete wall and displaying it in the form of an exterior damage map, the possibility of field application was demonstrated.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.45-54
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• 2019

The damage detection method using the extended Kalman filter(EKF) technique has been continuously used since EKF can estimation the responses of the damaged building structure and the stiffness of the structure. However, in the use of EKF, the requirement of setting the initial paramters P, Q, and R has caused the divergence and instability of the state vector, and various researches have been conducted to determine theses parameters. In this paper, adaptive extended Kalman filter(AEKF) method is proposed to solve the problem of setting the values of P, Q, and R, which are important parameters determining the convergence performance of the EKF state vector. By using the AEKF method proposed in this study, the P, Q, and R parameters are updated every k steps. The proposed algorithm is applied for the estimation of stiffness and the damage detection of 3-DOF problem. Based of the verification, it can be found that the selection process for the values of P, Q, and R can improve the convergence performance of EKF.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.6 s.99
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• pp.697-705
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• 2005

Vibration-based damage identification method using embedded sensitivity functions is discussed. The theory of embedded sensitivity functions is reviewed and applied to identify damage in a three degree-of-freedom system and a metallic panel. Embedded sensitivity functions are algebraic combinations of measured frequency response functions that reflect changes in the response of mechanical systems when mass, damping or stiffness parameters are changed. By comparing the embedded sensitivity functions with finite difference functions using undamaged and damaged frequency response functions, damage is shown to be properly detected, located and quantified in theory and practice assuming that structures of interest are only damaged in one location. Simulated and experimental results indicate that the technique is most effective when changes to frequency response functions are small to avoid distorsions in the estimated perturbations due to variations in the sensitivity functions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.387-392
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• 2019

A technique was researched to detect bolt looseness using a transfer impedance technique (the dual piezoelectric material technique) for monitoring the structural health of a bolt joint. In order to use the single piezoelectric material technique, an expensive impedance analyzer should be used. However, in the transfer impedance technique, low-cost fault detection can be performed using a general function generator and a digital multimeter. A steel plate frame test specimen composed of bolt joints was fabricated, and the tightening torques of the bolts were loosened step by step. By using the transfer impedance method, the damage index was obtained. It was found that the presence of faults could be reasonably estimated using the damage index, which increased with the degree of bolt looseness. An experiment was performed on the same specimen using the single piezoelectric material technique, and the results showed a similar tendency. It could be possible to estimate the damage of a bolt joint at low cost by eliminating the expensive impedance analyzer. This method could be used effectively for structural health monitoring after carrying out a study to estimate the fault location and severity.