• 한국구조물진단유지관리공학회 논문집
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• 제18권3호
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• pp.101-107
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• 2014

구조물의 손상 추정은 동적응답신호로부터 고유주기와 모드형상을 구한 후 이를 역해석하여 손상위치와 손상정도를 파악함으로써 이루어 진다. 건축구조물의 경우 토목구조물에 비하여 구조형식이 복잡하고 비구조요소 및 노이즈 등의 영향으로 인하여 구조물 판별에 어려움이 있다. 동적응답신호를 이용한 건물의 손상추정에 관한 최근의 연구들은 손상추정을 위하여 민감도 또는 추정치 등 간접적 지표를 사용하고 있으나, 좀 더 합리적이고 명확한 손상추정을 위하여 운동방정식으로부터 직접 유도된 변수를 손상지수로 활용할 필요가 있을 것으로 판단된다. 따라서 본 연구에서는 전단형 건물의 운동방정식으로부터 직접 유도된 층강성 감소비를 손상지수로 하는 손상추정 방법을 제안하였다. 제안된 손상지수는 손상 전 모드형상과 손상 전 후 고유진동수 차이를 알면 구할 수 있다. 제안된 손상 추정방법을 수치해석예제에 적용한 결과 손상이 발생한 층에서 층강성 변화율이 (-)부호를 나타내었으며, 크기가 다른 층에 비하여 15배 정도 크게 나타나 전단형 건물의 손상 추정지수로서 활용될 수 있을 것으로 판단된다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 춘계학술대회논문집
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• pp.583-589
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• 2001

For several decades many researchers have studied various algorithms, known as non-destructive testing, to identify abnormalities within a structure. Damage detection technique using vibration signal is a kind of these methods. Many researchers have published lots of papers dealing vibration signal to identify structural damage. All the methods for damage detection using vibration signal can be divided into two big categories. The first category is the method that requires some reference model such as finite element model, and the second is the method that does not require any reference model but needs only experimental data. This paper will be devoted to classify damage detection methods that utilize vibration signal.

• 비파괴검사학회지
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• 제32권3호
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• pp.291-295
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• 2012

In the industrial field, real-time monitoring system like a fault early detection is very important. For this, the infrared thermography technique as a new diagnosis method is proposed. This study is focused on the damage detection and temperature characteristic analysis of ball bearing using the non-destructive infrared thermography method. In this paper, thermal image and temperature data were measured by a Cedip Silver 450 M infrared camera. Based on the results, the temperature characteristics under the conditions of normal, loss lubrication, damage, dynamic loading, and damage under loading were analyzed. It was confirmed that the infrared technique is very useful for the detection of the bearing damage.

• Smart Structures and Systems
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• 제12권6호
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• pp.679-694
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• 2013

In this paper the application of the Interpolation Damage Detection Method to the numerical model of a suspension bridge instrumented with a network of Micro-Electro-Mechanical System sensors is presented. The method, which, in its present formulation, belongs to Level II damage identification method, can identify the presence and the location of damage from responses recorded on the structure before and after a seismic damaging event. The application of the method does not require knowledge of the modal properties of the structure nor a numerical model of it. Emphasis is placed herein on the influence of recorded signals noise on the reliability of the results given by the Interpolation Damage Detection Method. The response of a suspension bridge to seismic excitation is computed from a numerical model and artificially corrupted with random noise characteristic of two families of Micro-Electro-Mechanical System accelerometers. The reliability of the results is checked for different damage scenarios.

• 한국BIM학회 논문집
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• 제9권1호
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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.

• 대한토목학회논문집
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• 제26권4A호
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• pp.693-700
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• 2006

정적 손상 탐지방법은 동적 방법과 비교해서 실제 적용하기에 단순하고 효과적이다. 본 논문에서는 정적데이타를 이용하는 방법으로 변위, 처짐각, 곡률을 이용한 강박스 교량의 손상 탐지 방법에 대해서 연구하였다. 변위는 유한요소 해석에서 얻고, 처짐각과 곡률은 변위로부터 중앙차분법을 이용하여 구하였다. 손상되지 않은 경우와 손상된 경우의 응답차의 절대값으로 손상의 위치를 탐지하였다. 손상은 박스의 모서리 균열을 singular 요소를 사용하여 직접 모델링하여, 실질적인 거동을 분석하였다. 해석 결과 응답차의 절대값으로 손상의 위치를 탐지하기에 매우 효과적이었다.

• 한국구조물진단유지관리공학회 논문집
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• 제7권3호
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• pp.147-156
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• 2003

본 논문에서는 모드형상을 이용한 트러스 구조물의 손상탐지 방법을 소개하였다. 트러스 부재에 대한 손상탐지 이론은 손상 전과 손상 후의 모달 변형에너지의 차이점을 이용하여 정립하였으며, 이론의 타당성을 조사하기 위하여 1:6 축척의 6각형 트러스 구조물의 실험 데이터에 이론을 적용하였다. 손상 실험은 총 17가지의 시나리오로 구성되어 있으며, 손상 타입은 3가지로 구성되어있다. 17가지 실험 데이터에 대한 손상평가 결과, 본 연구에서 제안한 방법으로 트러스 부재의 손상을 성공적으로 탐지할 수 있었으며, 비교적 작은 손상의 경우 계측 데이터의 노이즈가 손상탐지 성능에 많은 영향을 미친다는 것을 확인하였다.

• Smart Structures and Systems
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• 제12권3_4호
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• pp.309-325
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• 2013

Environmental and operational variables are inevitable concerns by researchers and engineers when implementing the damage detection algorithm in practical projects, because the change of structural behavior could be masked by the conditions in a large extent. Thus, reliable damage detection methods should have a virtue of immunity from environmental and operational variables. In this paper, the pair cointegration method was presented as a novel way to remove the effect of environmental variables. At the beginning, the concept and procedure of this approach were introduced, and then the theoretical formulation and numerical simulations were put forward to illustrate the feasibility. The jump exceeding the control limit in the residual indicates the occurrence of damage, while the direction and magnitude imply the most potential damage location. In addition, the simulation results show that the proposed method has strong ability to resist the noise.

• Smart Structures and Systems
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• 제2권2호
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• pp.141-154
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• 2006

Recently, the Hilbert-Huang transform (HHT) has gained considerable attention as a novel technique of signal processing, which shows promise for the system identification and damage detection of structures. This study investigates the effectiveness and accuracy of the HHT method for the system identification and damage detection of structures through a series of experiments. A multi-degree-of-freedom (MDOF) structural model has been constructed with modular members, and the columns of the model can be replaced or removed to simulate damages at different locations with different severities. The measured response data of the structure due to an impulse loading is first decomposed into modal responses using the empirical mode decomposition (EMD) approach with a band-pass filter technique. Then, the Hilbert transform is subsequently applied to each modal response to obtain the instantaneous amplitude and phase angle time histories. A linear least-square fit procedure is used to identify the natural frequencies and damping ratios from the instantaneous amplitude and phase angle for each modal response. When the responses at all degrees of freedom are measured, the mode shape and the physical mass, damping and stiffness matrices of the structure can be determined. Based on a comparison of the stiffness of each story unit prior to and after the damage, the damage locations and severities can be identified. Experimental results demonstrate that the HHT method yields quite accurate results for engineering applications, providing a promising tool for structural health monitoring.

• Structural Engineering and Mechanics
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• 제33권3호
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• pp.325-337
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• 2009

Structural damage detection, damage localization and severity estimation of jacket platforms, based on calculating modal strain energy is presented in this paper. In the structure, damage often causes a loss of stiffness in some elements, so modal parameters; mode shapes and natural frequencies, in the damaged structure are different from the undamaged state. Geometrical location of damage is detected by computing modal strain energy change ratio (MSECR) for each structural element, which elements with higher MSECR are suspected to be damaged. For each suspected damaged element, by computing cross-modal strain energy (CMSE), damage severity as the stiffness reduction factor -that represented the ratios between the element stiffness changes to the undamaged element stiffness- is estimated. Numerical studies are demonstrated for a three dimensional, single bay, four stories frame of the existing jacket platform, based on the synthetic data that generated from finite element model. It is observed that this method can be used for damage detection of this kind of structures.