• Journal of the Earthquake Engineering Society of Korea
• /
• v.2 no.1
• /
• pp.35-46
• /
• 1998

Structural damage is used to be modeled through reductions in the stiffness of structural elements for the purpose of damage estimation of structural system. In this study, the concept of joint damage is employed for more realistic damage assessment of a steel structure. The joint damage is estimated damage based on the mode shape informations using neural networks, The beam-to-column connection in a steel frame structure is represented by a rotational spring at the fixed end of a beam element. The severity of joint damage is defined as the reduction ratio of the connection stiffness with respect to the value of the intact joint. The concept of the substructural identification is used for the localized damage assessment in a large structure. The feasibility of the proposed method is examined using an example with simulated data. It has been found that the joint damages can be reasonably estimated for the case with the measurements of the mode vectors subjected to noise.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.1A
• /
• pp.135-146
• /
• 2008

In this paper, a hybrid damage monitoring scheme for prestressed concrete (PSC) girder bridges by using sequential acceleration and impedance signatures is newly proposed. Damage types of interest include prestress-loss in tendon and flexural stiffness-loss in a concrete girder. The hybrid scheme mainly consists of three sequential phases: damage alarming, damage classification, and damage estimation. In the first phase, the global occurrence of damage is alarmed by monitoring changes in acceleration features. In the second phase, the type of damage is classified into either prestress-loss or flexural stiffness-loss by recognizing patterns of impedance features. In the third phase, the location and the extent of damage are estimated by using two different ways: a mode shape-based damage detection to detect flexural stiffness-loss and a natural frequency-based prestress prediction to identify prestress-loss. The feasibility of the proposed scheme is evaluated on a laboratory-scaled PSC girder model for which hybrid vibration-impedance signatures were measured for several damage scenarios of prestress-loss and flexural stiffness-loss.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.6 no.3
• /
• pp.41-52
• /
• 2002

In the companion paper, nonlinear finite element analysis procedures are presented for the seismic damage evaluation of RC bridge piers. This paper defines a damage index based on the predicted hysteretic behavior of a RC bridge pier. Damage indices aim to provide a means of quantifying numerically the damage in RC bridge piers sustained under earthquake loading. The proposed numerical method is applied to RC bridge piers tested by other, and compared to existing damage indices. The proposed numerical method gives a realistic prediction of damage throughout the loading cycles for several test specimens investigated.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.3 no.3
• /
• pp.9-20
• /
• 1999

A method is proposed to estimate the joint damages of a steel structure from modal data using the neural networks technique. The beam-to-column connection in a steel frame structure is represented by a zero-length rotational spring of the end of the beam element, and the connection fixity factor is defined based on the rotational stiffness so that the factor may be in the range 0~1.0. Then, the severity of joint damage is defined as the reduction ratio of the connection fixity factor. Several advanced techniques are employed to develop the robust damage identification technique using neural networks. The concept of the substructural indentification is used for the localized damage assessment in the large structure. The noise-injection learning algorithm is used to reduce the effects of the noise in the modal data. The data perturbation scheme is also employed to assess the confidence in the estimated damages based on a few sets of actual measurement data. The feasibility of the proposed method is examined through a numerical simulation study on a 2-bay 10-story structure and an experimental study on a 2-story structure. It has been found that the joint damages can be reasonably estimated even for the case where the measured modal vectors are limited to a localized substructure and the data are severely corrupted with noise.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1996.06a
• /
• pp.229-232
• /
• 1996

본 논문에서는 공간적 보간을 응용하여 손상된 영상 구획의 데이터를 복원하는 기법을 제시한다. 이러한 기법은 손상된 영상을 부가 정보 없이 복원하는 오류 은폐의 핵심으로 Park[3], Wang[4], Sun[9], Lee[7], Hemami[8] 등에 의해서 여러 가지 기법들이 제안되었다. 그러나 이러한 기법들은 단순히 주변 구획과의 경계면에서의 연속성만을 고려하여 복원하므로 구획 내부의 데이터를 복원하는데 한계가 있으며 계산량도 많은 단점이 있다. 따라서 본 논문에서는 이러한 기존의 기법들의 단점을 극복하기 위하여 Non-Unform Rational B-Spline(NURBS)을 응용한 복원 기법을 제안한다. 제시된 주변 구획의 오류 유무와 윤곽선의 방향에 따라 주변 구획의 화소 정보에 할당되는 가중치를 적절히 변경하여 NURBS를 적용한다. 따라서 윤곽선의 방향을 더욱 견실하게 복원함으로써 주관적, 객관적 관점에서 기존의 기법보다 우수한 영상 구획 복원 성능을 얻을 수 있다. 정지 영상에 대한 컴퓨터 모의 실험 결과 제안하는 알고리듬을 기존의 기법보다 30% 구획 손실율에서 0.5 dB이상 성능 향상을 얻을 수 있음을 관찰하였다.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2010.04a
• /
• pp.692-695
• /
• 2010

일반적으로 모델개선에서는 부재단위의 강성을 파악하기 때문에 구조물의 취약부인 부재단부의 손상이 집중될 경우 손상의 형태를 세밀히 파악하기 어려우며 손상된 구조물의 거동을 정확하게 모사하기 어려운 단점이 있었다. 이를 해결하기 위해서는 부재 단부에 발생한 손상을 고려할 수 있는 좀 더 정밀한 해석 모델을 통한 모델개선이 필요하다. 본 연구에서는 부재 단부에 반강접 접합을 가지는 해석모델을 사용해 모델 개선을 실시하고 이를 통해 접합부의 손상 평가와 손상 구조물의 거동을 파악하였다. 제안된 방법을 5층 1경간의 RC 벽식 실험체의 손상탐지에 적용하였으며 그 결과 부재단위 모델을 사용할 때보다 더욱 정확하게 구조물의 손상을 평가하고 거동을 모사할 수 있었다.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.28 no.4
• /
• pp.417-423
• /
• 2015

In this study, Magnetic Flux Leakage(MFL)-based inspection system was applied to detect the local fault of wire rope. To verify the feasibility of the proposed damage detection technique, an 4-channel MFL sensor head prototype was designed and fabricated. A wire rope with several types of cross-sectional damages were fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the wire rope specimen. To interpret the condition of the wire rope, magnetic flux signals were used to determine the locations of the flaws. To improve the resolution of signal, the instantaneous variation value of magnetic flux was utilized. Measured signals from the damaged specimen were compared with thresholds set for objective decision making. Finally, the results were compared with information on actual inflicted damages to confirm the accuracy and effectiveness of the proposed cable monitoring method.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.9 no.5
• /
• pp.9-13
• /
• 2009

Modal parameters including resonant frequencies and mode shapes are heavily utililized in most damage identification throries for structural health monitoring. However, extracting modal parameters from dynamic responses needs postprocessing which inevitably involves errors in curve-fitting resonants as well as transforming the domain of responses. In this paper, the applicability of a damage identification method based on free vibration responses to the in-sevice responses is experimentally verified. The experiment is performed via applying periodic and nonperiodic moving loads to a simply supported beam and displacement responses are measured. The moving load is simulated using steel balls and a downhill device. The damage identification results show that the in-service response may be applicable to identifying damage in the beam.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.16 no.2
• /
• pp.87-94
• /
• 2012

A damage estimation method of wind turbine tower using natural frequency and mode shape is presented for effective condition monitoring. Dynamic analysis for a wind turbine was carried out to obtain the response of tower from which modal properties were identified. A neural network was learned based on training patterns generated by the changes of natural frequency and mode shape due to various damages. The changes of modal property were calculated using a program for modal parameter estimation. Damage locations and severities could be successfully estimated for 10 damage cases including multi-damage cases using the trained neural network. The damage severities for very small damages generally tends to be slightly under-estimated however, the identified damage locations agreed reasonably well with the accurate locations. Enhancement of the estimation result for very small damage and verification of the proposed method through experiment will be carried out by further study.

• Proceedings of the Earthquake Engineering Society of Korea Conference
• /
• 2002.03a
• /
• pp.159-168
• /
• 2002

A recently developed filbert-Huang transform (HHT) technique is applied to detect damage locations of bridge structures. The HHT may be used to identify the locations of damages which exhibit nonlinear and nonstationary behavior, since the HHT can show the instantaneous frequency characteristics of the signal. A series of numerical simulations were conducted for bridge pier systems with damages under a controlled load with sweeping frequency. The results of the numerical simulation study indicate that the HHT method can reasonably identify damage locations using a limited number of acceleration sensors under severe measurement noise condition.