• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2000년도 봄 학술발표회논문집
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• pp.297-303
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• 2000

Damage estimation of a bridge structure is presented using ambient vibration data caused by the traffic loadings. The procedure consists of identification of the modal properties and assessment of the damage locations and severities. An experimental study is carried out on the bridge model subjected to vehicle loadings. Vertical accelerations of the bridge deck are measured at a limited number of locations. The modal parameters are identified from the free vibration signals extracted using the random decrement method. Then, the damage assessment is carried out based on the estimated modal parameters using the neural networks technique. The identified damage locations and severities agree reasonably well with the inflicted damages on the structure.

• Earthquakes and Structures
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• 제3권2호
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• pp.117-140
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• 2012

The proposed research includes a comprehensive study on the seismic vulnerability assessment of typical building types, representative of the structural materials, the seismic codes and the construction techniques of Southern Europe. A damage database is created after the elaboration of the results of the observational data obtained from post-earthquake surveys carried out in the area struck by the September 7, 1999 Athens earthquake, a near field seismic event in an extended urban region. The observational database comprises 180.945 buildings which developed damage of varying degree, type and extent. The dataset is elaborated in order to gather useful information about the structural parameters influence on the seismic vulnerability and their correlation to the type and degree of building damages in near field earthquakes. The damage calibration of the observational data was based on label - damage provided by Earthquake Planning and Protection Organization (EPPO) in Greece and referred to the qualitative characterization for the recording of damage in post-earthquake surveys. Important conclusions are drawn on the parameters that influence the seismic response based on the wide homogeneous database which adds to the reliability of the collected information and reduces the scatter on the produced results.

• 한국정밀공학회지
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• 제29권5호
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• pp.531-537
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• 2012

Fretting fatigue tests were conducted to investigate the effect of contact pressure on fretting fatigue behavior in aluminum alloy A7075-T6. Test results showed that when the contact pressure is so low that gross or partial slip occurs at the pad/specimen interface, fretting fatigue damage increases with the contact pressure. However, when the contact pressure is high enough to prevent slip at the interface, fretting fatigue damage decreases with the contact pressure. In order to understand how the contact pressure influence the fretting fatigue damage, finite element analyses were conducted and the analysis results were used to evaluate critical plane fretting fatigue damage parameters and their components. It is revealed that fretting fatigue damage estimated with the parameters exhibits the same variation as that in the tests. Moreover, the variation of fretting fatigue damage is closely related with that of the maximum normal stress on the critical plane rather than the strain amplitude on the critical plane.

• Structural Engineering and Mechanics
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• 제82권6호
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• pp.771-783
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• 2022

Structural damage identification (SDI) methods have been proposed to monitor the safety of structures. However, the traditional SDI methods using modal parameters, such as natural frequencies and mode shapes, are not sensitive enough to structural damage. To tackle this problem, this paper proposes a new SDI method based on transmissibility assurance criterion (TAC) and weighted Schatten-p norm regularization. Firstly, the transmissibility function (TF) has been proved a useful damage index, which can effectively detect structural damage under unknown excitations. Inspired by the modal assurance criterion (MAC), TF and MAC are combined to construct a new damage index, so called as TAC, which is introduced into the objective function together with modal parameters. In addition, the weighted Schatten-p norm regularization method is adopted to improve the ill-posedness of the SDI inverse problem. To evaluate the effectiveness of the proposed method, some numerical simulations and experimental studies in laboratory are carried out. The results show that the proposed method has a high SDI accuracy, especially for weak damages of structures, it can precisely achieve damage locations and quantifications with a good robustness.

• Structural Monitoring and Maintenance
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• 제2권1호
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• pp.77-93
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• 2015

The idea of using measured dynamic characteristics for damage detection is attractive because it allows for a global evaluation of the structural health and condition. However, vibration-based damage detection for complex structures such as long-span cable-supported bridges still remains a challenge. As a suspension or cable-stayed bridge involves in general thousands of structural components, the conventional damage detection methods based on model updating and/or parameter identification might result in ill-conditioning and non-uniqueness in the solution of inverse problems. Alternatively, methods that utilize, to the utmost extent, information from forward problems and avoid direct solution to inverse problems would be more suitable for vibration-based damage detection of long-span cable-supported bridges. The auto-associative neural network (ANN) technique and the probabilistic neural network (PNN) technique, that both eschew inverse problems, have been proposed for identifying and locating damage in suspension and cable-stayed bridges. Without the help of a structural model, ANNs with appropriate configuration can be trained using only the measured modal frequencies from healthy structure under varying environmental conditions, and a new set of modal frequency data acquired from an unknown state of the structure is then fed into the trained ANNs for damage presence identification. With the help of a structural model, PNNs can be configured using the relative changes of modal frequencies before and after damage by assuming damage at different locations, and then the measured modal frequencies from the structure can be presented to locate the damage. However, such formulated ANNs and PNNs may still be incompetent to identify damage occurring at the deck members of a cable-supported bridge because of very low modal sensitivity to the damage. The present study endeavors to enhance the damage identification capability of ANNs and PNNs when being applied for identification of damage incurred at deck members. Effort is first made to construct combined modal parameters which are synthesized from measured modal frequencies and modal shape components to train ANNs for damage alarming. With the purpose of improving identification accuracy, effort is then made to configure PNNs for damage localization by adapting the smoothing parameter in the Bayesian classifier to different values for different pattern classes. The performance of the ANNs with their input being modal frequencies and the combined modal parameters respectively and the PNNs with constant and adaptive smoothing parameters respectively is evaluated through simulation studies of identifying damage inflicted on different deck members of the double-deck suspension Tsing Ma Bridge.

• Structural Engineering and Mechanics
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• 제7권4호
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• pp.387-400
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• 1999

Damage detection in civil engineering structures using the change in dynamic system parameters has gained a lot of scientific interest during the last decade. By repeating a dynamic test on a structure after a certain time of use, the change in modal parameters can be used to quantify and qualify damages. To be able to use the modal parameters confidentially for damage evaluation, the effect of other parameters such as excitation type, ambient conditions,... should be considered. In this paper, the influence of excitation type on the dynamic system parameters of a highway prestressed concrete bridge is investigated. The bridge, B13, lies between the villages Vilvoorde and Melsbroek and crosses the highway E19 between Brussels and Antwerpen in Belgium. A drop weight and ambient vibration are used to excite the bridge and the response at selected points is recorded. A finite element model is constructed to support and verify the dynamic measurements. It is found that the difference between the natural frequencies measured using impact weight and ambient vibration is in general less than 1%.

• 대한기계학회논문집A
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• 제24권3호
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• pp.634-644
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• 2000

Fatigue crack growth and life is estimated by various fracture mechanical parameters but affected by load, material and environment. Fatigue character of component without surface notch cannot be e valuated by above-mentioned parameters due to microstructure of in-service material. Single fracture mechanical parameter or nondestructive parameter cannot predict fatigue damage in arbitrary boundary condition but multiple fracture mechanical parameters or nondestructive parameters can Fatigue crack growth modelling with three point representation scheme uses this merit but has limit on real-time monitoring. Therefore, this study shows fatigue damage model using backpropagatior. neural networks on the basis of X-ray half breadth ratio B/$B_o$ fractal dimension $D_f$ and fracture mechanical parameters can predict fatigue crack growth rate da/dN and cycle ratioN/$N_f$ at the same time within engineering estimated mean error(5%).

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1991년도 봄 학술발표회 논문집
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• pp.61-67
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• 1991

Conventional aseismic design methods of reinforced concrete frame all but disregard the state of damage over the entire building frame. This paper presents an automated damage-contorlled design method, which aims for uniform damage distribution throughout the entire building frame, as measured by the individual mumber damage indexes. Three design parameters, namely the longitudinal steel ratio, the confinement steel ratio and the frame member depth, were studied for their influence on the frame responce to an earthquake. The usefulness of this design method is demonstrated with a four story example office building predicting the extent of structural damage.

• 한국공작기계학회논문집
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• 제10권4호
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• pp.14-21
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• 2001

To estimate crack growth rate and cycle ratio uniquely, many investigators have developed various kinds of mechanical parameters and theories. But, thes have produced local solution space through single parameter. Neural Networks can perform patten classification using several input and output parameters. Fatigue damage model by neural networks was used to recognize the relation between da/dN/N/N(sub)f, and half-value breadth ratio B/Bo, fractal dimension D(sub)f, and fracture mechanical parameters in 2024-T3 aluminium alloy. Learned neural networks has ability to predict both crack growth rate da/dN and cycly ratio /N/N(sub)f within engineering estimated mean error(5%).

• 한국지반공학회논문집
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• 제20권7호
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• pp.15-24
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• 2004

본 논문은 1994 Northridge 지진에 의해 발생된 주거건물손상에 관하여 건물 교체시의 가격에 대한 상대적 수리비용의 개념으로 GIS기반의 손상평가에 관하여 기술하였다. 빌딩손상은 164개의 서로 다른 지역에서 얻어진 지진기록으로부터 유도된 지진매개변수와 빌딩위치 및 안전조사보고서를 바탕으로 평가하였다. 본 논문은 가장 심한 건물피해를 받은 위치를 규명하는 인식 알고리즘이 GIS를 통하여 개발되었다. 이러한 알고리즘은 지진 후 신속한 응급조치와 위성으로부터 얻어진 데이터를 짧은 시간에 분석할 수 있는 프레임을 제공한다.