• 한국지진공학회논문집
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• 제8권6호통권40호
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• pp.73-80
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• 2004

구조물의 손상 진단을 위해 측정 가속도 데이터를 사용한 비선형 시간영역 SI 알고리듬을 개발하였다. 구조물의 비선형 거동을 고려하기 위하여 측정 가속도 증분과 해석에 의한 가속도 증분의 차이로 출력오차를 정의하고, 구속 비선형 최적화 문제를 풀어 최적 구조변수를 구하였다. 개발된 알고리듬은 시간에 따라 변하는 강성도와 감쇠 변수를 추정하도록 하였다. 구조물의 비선형 거동에 의한 복원력은 추정된 시간에 따라 변하는 구조변수와 Newmark-$\beta$법으로 계산한 변위를 사용하여 복원하였으며, 복원 과정에서 비탄성 거동에 대한 어떤 모델도 사전에 설정하지 않았다. 개발한 알고리듬에서는 측정오차와 공간 및 상태에 대한 불완전 측정의 경우를 고려하였다. 개발한 알고리듬을 검증하기 위하여 3층 전단건물에 대한 수치 모의시험과 실내 모형실험을 통한 연구를 수행하였다.

• 한국구조물진단유지관리공학회 논문집
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• 제11권4호
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• pp.129-137
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• 2007

본 논문에서는 교량상을 이동하는 차량의 차축하중을 교량의 동적거동을 계측하여 추정하는 알고리듬을 제안하였으며, 교량을 보로 모델하여 알고리듬을 적용하였다. 가속도는 교량에서 직접 계측하였으며, 변위는 가속도와 같은 위치에 부착한 변형률을 변환하여 계산하는 식을 제안하였다. 절점하중벡터는 속도별로 준비해둔 절점하중변환행렬 데이터베이스를 사용하여 구하였다. 개발된 알고리듬을 수치예제와 실내모형실험을 통해 검증하였다. 수치예제에서는 계측오차와 속도 및 위치오차가 하중식별에 미치는 영향을 분석하였다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1992년도 봄 학술발표회 논문집
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• pp.89-94
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• 1992

구조물의 비탄성 지진응답을 예측하기 위하여 수행되는 진동대 실험(Shaking Table Test)과 준정적 실험(Quasic-Static Test)의 각 장점을 조합한 유사동적 실험(Pseudodynamic Test)은 실물 크기 구조물의 비탄성 거동온 파악하는 데 널리 사용되고 있다. 이러한 유사동적 실험에서는 구조물에 변위이력의 정확한 가력 및 측정이 가장 중요하다. 측정된 변위와 계산된 변위의 차를 조절오차(Control Error)라고 하며, 임의의 단계에서 측정된 변위를 조정하므로서 그 다음 단계의 조절오차 및 측정오차(Measurement Error)를 감소시킬 수 있다. 따라서 개선된 유사동적 실험의 알고리즘을 얻을 수 있다.

• 대한기계학회논문집A
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• 제26권2호
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• pp.254-259
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• 2002

A variable air-gap type system is widely used for inductive precision position measurement systems. This type transducer has high sensitivity but lacks a linear measurement range due to structural nonlinearity. Furthermore, as measurement range increases, linearity error is also increased. The alternative is a variable overlap-area type system. The sensitivity of this type is determined by the initial air-gap dimension, keeps the original value and does not deteriorate linearity in spite of the variations of the measuring range.

• Journal of Mechanical Science and Technology
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• 제16권11호
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• pp.1359-1366
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• 2002

The measurement of residual stresses by the hole-drilling method has been used to evaluate residual stresses in structural members. In this method, eccentricity can usually occur between the hole center and rosette gage center. In this study, we obtained the magnitude of the error due to eccentricity of a hole through the finite element analysis. To predict the magnitude of the error due to eccentricity of a hole in the biaxial residual stress field, it could be learned through the back propagation neural network. The prediction results of the error using the trained neural network showed good agreement with FE analyzed results.

• 대한기계학회논문집A
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• 제26권3호
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• pp.436-444
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• 2002

The measurement of residual stresses by the hole-drilling method has been commonly used to evaluate residual stresses in structural members. In this method, eccentricity can usually occur between the hole center and rosette gage center. In this study, the error due to the hole eccentricity is predicted using the artificial neural network. The neural network has trained training examples of stress ratio, normalized eccentricity, off-centered direction and stress error using backpropagation learning process. The prediction results of the error using the trained neural network are good agreement with FE analyzed ones.

• 대한기계학회논문집A
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• 제26권12호
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• pp.2475-2482
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• 2002

The measurement of residual stresses by the hole-drilling method has been commonly used to evaluate residual stresses in structural members. In this method, eccentricity can usually occur between the hole center and rosette gage center. In this study, the error due to the hole eccentricity is compensated using the neural network. The neural network has trained training examples of normalized eccentricity, eccentric direction and direction of maximum stress at eccentric case using backpropagation learning process. The trained neural network could compensated the error of measured residual stress in experiments with hole eccentricity. The proposed neural network is very useful for compensation of the error due to hole eccentricity in hole-drilling method.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.412-418
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• 2001

The measurement of residual stresses by the hole-drilling method has been commonly used to evaluate residual stresses in structural members. In this method, eccentricity can usually occur between the hole center and rosette gage center. In this study, the error due to the hole eccentricity is corrected using the neural network. The neural network has trained training examples of normalized eccentricity, eccentric direction and direction of maximum stress at eccentric case using backpropagation learning process. The trained neural network could corrected the error of measured residual stress in experiments with hole eccentricity. The proposed neural network is very useful for correction of the error due to hole eccentricity in hole-drilling method.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집A
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• pp.956-963
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• 2001

The measurement of residual stresses by the hole-drilling method has been commonly used to evaluate residual stresses in structural members. In this method, eccentricity can usually occur between the hole center and rosette gage center. In this study, the error due to the hole eccentricity is predicted using the artificial neural network. The neural network has trained training examples of stress ratio, normalized eccentricity, off-centered direction and stress error using backpropagation loaming process. The prediction results of the error using the trained neural network are good agreement with FE analyzed ones.

• Computers and Concrete
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• 제5권1호
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• pp.37-60
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• 2008

Structural health monitoring of existing infrastructure is currently an important field of research, where elaborate experimental programs and advanced analytical methods are used in identifying the current state of health of critical and important structures. The paper outlines two methods of system identification of beam-like reinforced concrete structures representing bridges, through static measurements, in a distributed damage scenario. The first one is similar to the stiffness method, re-cast and the second one to flexibility method. A least square error (LSE) based solution method is used for the estimation of flexural rigidities and damages of simply supported, cantilever and propped cantilever beam from the measured deformation values. The performance of both methods in the presence of measurement errors is demonstrated. An experiment on an un-symmetrically damaged simply supported reinforced concrete beam is used to validate the developed method. A method for damage prognosis is demonstrated using a generalized, indeterminate, propped cantilever beam.