• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.5
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• pp.345-352
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• 2016

As aircrafts are being operated at high altitude, wing structures experience various fatigue loadings under cryogenic environments. As a result, fatigue damage such as a crack could be develop that could eventually lead to a catastrophic failure. For this reason, fatigue damage monitoring is an important process to ensure efficient maintenance and safety of structures. To implement damage detection in real-world flight environments, a special cooling chamber was built. Inside the chamber, the temperature was maintained at the cryogenic temperature, and harmonic fatigue loading was given to a wing structure. In this study, piezoelectric active-sensing based guided waves were used to detect the fatigue damage. In particular, a beamforming technique was applied to efficiently measure the scattering wave caused by the fatigue damage. The system was used for detection, growth monitoring, and localization of a fatigue crack. In addition, a sensor diagnostic process was also applied to ensure the proper operation of piezoelectric sensors. Several experiments were implemented and the results of the experiments demonstrated that this process could efficiently detect damage in such an extreme environment.

• Journal of the Korean Society for Railway
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• v.14 no.4
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• pp.320-326
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• 2011

This paper proposes a baseline-free SHM technique in which the time-reversal process of Lamb waves and the imaging method are used. The proposed SHM technique has three distinct features when compared with the authors' previously proposed one: (1) It use the reconstructed signal for damage diagnosis, without need to extract the damage signal as the difference between reconstructed signal and initial input signal; (2) It use the imaging method based on the time-offlight information from the reconstructed signal, instead of using a pattern comparison method; (3) In order to make the damage image more clear, the modified mathematical definition of damage image in a pixel is used. The proposed SHM technique is evaluated through the damage detection experiment for an aluminum plate with damage at different locations.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.195-198
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• 2011

석유 및 천연가스 생산에 사용되는 고정식 해양플랜트에는 자켓 구조물이 가장 많이 사용되고 있다. 생산에 사용되는 자켓 구조물은 풍하중이나 파랑하중에 의해 인명의 피해 없이 변위 및 응력에 대해 안전해야 한다. 그러나 1940년대 후반부터 사용되어 온 자켓 구조물은 피로하중, 노후화로 인해 내구성에 문제가 생기고 있다. 본 논문에서는 자켓 구조물의 안전성을 검토하기 위해 모드형상을 이용하여 자켓 구조물의 손상 위치를 탐색하는 방법을 제시한다. 제시한 손상탐지기법의 효용성을 입증하기 위해 자켓 구조물의 유한요소모델에 임의의 손상을 모사하였다. 유한요소모델의 손상 전 모드형상과 손상 후 모드형상의 모달 변형에너지의 변화를 이용하여 손상 지수를 유도하고 유도한 손상지수를 사용하여 손상이 있는 부재와 손상이 없는 부재를 분류하였다. 연구 결과 손상지수가 '0'인 부재를 제외한 나머지 부재 모두 본 연구에서 제시한 손상탐지기법으로 손상 부재를 판별할 수 있었다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.3
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• pp.31-38
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• 2003

In the present work, a nonlinear inverse perturbation method which has been used in the structural optimization, is adopted so as to identify the structural damages. Unlike the structural optimization, a larger number of constrained equations than the number of unknown parameters are often required detect structural damage. Therefore, nonlinear least squares method is utilized to solve the problem. Because only a limited number of sensors are available I real situation of damage detection, the determination of sensor location becomes one of the most important issues. Hence, this work concentrates on the issue of sensor placement in the framework of nonlinear inverse perturbation method, and the performances of various methodologies concerning to sensor placement are compared with each other. The comparisons show tat the successive elimination method gets good performance for sensor placement. From the several numerical studies, it is confirmed that the inverse perturbation method, combined with the successive elimination method, is very promising in structural damage detection.

• Computational Structural Engineering
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• v.27 no.4
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• pp.62-67
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• 2014

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.4
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• pp.283-293
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• 2024

In this study, advanced unscented Kalman filter (UKF) and particle filter (PF) implementations are introduced and applied to perform system identification (SI) for sudden structural damage induced by seismic loading. These two methods are then compared to validate their applicability to SI tasks. For this validation, the Bouc- Wen model is used to simulate the nonlinear shear-building response, and an adaptive rule (i.e., an adaptive tracking method) is applied to the two filter methods to improve their tracking performance during sudden changes in system properties. When the original UKF and PF are applied to an earthquake scenario, both methods fail to estimate the damage initiation time and post-damage parameter values. After applying the adaptive tracking method, it is found for both methods that although the occurrence time is identified, the estimation of the damage state is still not accurate. To improve the accuracy, an adjusted adaptive tracking method is applied, and the two methods then derive accurate estimates. Finally, when considering the computation time, UKF is promoted as a better choice for practical applications, provided that a proper adaptive tracking method is implemented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.265-271
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• 2018

This paper presents a method for detecting damage to a structure at low cost using its impedance. The impedance technique is a typical method to detect local damage for structural health monitoring. This is a common technique for estimating damage by monitoring the electro-mechanical admittance signal of the structure. To apply this technique, an expensive impedance analyzer is generally used. On the other hand, it is necessary to develop a low-cost variant to effectively disseminate the technique. In this study, a method based on the transfer impedance using a function generator and digital multimeter, which are generally used in the laboratory instead of an impedance analyzer, was developed. That is, this technique estimates the damage by comparing the damage index using the amplitude ratio of the output voltage measured in the healthy and damaged state. A transfer impedance test was carried out on a steel specimen. By comparing the damage index, the presence of damage could be assessed reasonably. This study is a basic investigation of an impedance-based low-cost damage detection method that can be used effectively for structural health monitoring if supplemented with future research to estimate the damage location and severity.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.1
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• pp.81-90
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• 2008

This study deals with a method to identify structural damage using the combined finite element method (FEM) and the advanced damage search technique. The novelty of this study is the application of plates with arbitrary damage shapes and their response due to the anomalies in a structure subjected to impact loading. The technique described in this paper may allow us not only to detect the stiffness distribution of the damaged areas but also to find locations and the extent of damage. To demonstrate the feasibility of the method, the algorithm is applied to a steel thin plate structures with an arbitrary damage shape. The results demonstrate the excellencies of the method from the standpoints of computation efficiency as well as its ability to investigate the arbitrary stiffness reductions.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.2 s.54
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• pp.69-79
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• 2007

In this paper, a technique to detect structural damage and estimate its severity using peaks and zeros of frequency response functions (FRFs) is developed. The peaks in FRFs represent the natural frequencies of the structure and the zeros provide additional information. The characteristics of peaks and zeros are defined and the calculation procedure to obtain the peaks and zeros from the relationship between frequency response function and stiffness and mass matrices are clearly explained. A structural system identification theory which is utilizing the sensitivity of stiffness of a structural member to eigenvalues, i.e., peaks and zeros, is established. The proposed method can identify damage location and its severity, with natural and zero frequencies, by estimating structural stiffness of the structure in the process of making a analytical model The accuracy and feasibility is demonstrated by numerical models of a spring-mass system and a beam structure.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.4
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• pp.253-263
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• 2021

Concrete structures are damaged by aging and external environmental factors. This type of damage is to appear in the form of cracks, to proceed in the form of spalling. Such concrete damage can act as the main cause of reducing the original design bearing capacity of the structure, and negatively affect the stability of the structure. If such damage continues, it may lead to a safety accident in the future, thus proper repair and reinforcement are required. To this end, an accurate and objective condition inspection of the structure must be performed, and for this inspection, a sensor technology capable of detecting damage area is required. For this reason, we propose a deep learning-based image processing algorithm that can detect spalling. To develop this, 298 spalling images were obtained, of which 253 images were used for training, and the remaining 45 images were used for testing. In addition, an improved loss function and data augmentation technique were applied to improve the detection performance. As a result, the detection performance of concrete spalling showed a mean intersection over union of 80.19%. In conclusion, we developed an algorithm to detect concrete spalling through a deep learning-based image processing technique, with an improved loss function and data augmentation technique. This technology is expected to be utilized for accurate inspection and diagnosis of structures in the future.