• Nuclear Engineering and Technology
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• 제49권1호
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• pp.245-253
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• 2017

The relative displacement of a piping system installed between isolated and nonisolated structures in a severe earthquake might be larger when without a seismic isolation system. As a result of the relative displacement, the seismic risks of some components in the building could increase. The possibility of an increase in seismic risks is especially high in the crossover piping system in the buildings. Previous studies found that an elbow which could be ruptured by low-cycle ratcheting fatigue is one of the weakest elements. Fatigue curves for elbows were suggested based on component tests. However, it is hard to find a quantitative evaluation of the ultimate state of piping elbows. Generally, the energy dissipation of a solid structure can be calculated from the relation between displacement and force. Therefore, in this study, the ultimate state of the pipe elbow, normally considered as failure of the pipe elbow, is defined as leakage under in-plane cyclic loading tests, and a failure estimation method is proposed using a damage index based on energy dissipation.

• 정보처리학회논문지B
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• 제10B권7호
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• pp.811-814
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• 2003

본 논문에서는 십자패턴과 육각패턴을 이용한 고속 블록 정합 동작 예측 기법을 제안한다. 블록 기반 탐색에서 전역 탐색방법이 가장 좋은 동작벡터를 찾지만, 탐색영역 내의 모든 전을 검색하기 때문에 많은 시간을 필요로 하게 된다. 본 방법은 대부분의 동영상에서 동작벡터가 블록의 중심 부근에 집중적으로 분포함을 착안하여 십자패턴으로 중앙을 우선 탐색한 다음 움직임이 큰 동작벡터를 육각패턴을 사용하여 찾는다. 실험결과, 본 방법은 기존의 탐색방법보다 화질과 탐색시간에서 대부분의 경우에 좋은 성능을 보임을 알 수 있다.

• Smart Structures and Systems
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• 제26권6호
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• pp.735-751
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• 2020

Identification of structure parameters is crucial in Structural Health Monitoring (SHM) context for activities such as model validation, damage assessment and signal processing of structure response. In this paper, guided waves generated by piezoelectric transducers are used for in-situ and non-destructive structural parameter estimation based on Bayesian approach. As Bayesian approach needs iterative process, which is computationally expensive, this paper proposes a method in which an analytical model is selected and developed in order to decrease computational time and complexity of modeling. An experimental set-up is implemented to estimate three target elastic and geometrical parameters: Young's modulus, Poisson ratio and thickness of aluminum and steel plates. Experimental and simulated data are combined in a Bayesian framework for parameter identification. A significant accuracy is achieved regarding estimation of target parameters with maximum error of 8, 11 and 17 percent respectively. Moreover, the limitation of analytical model concerning boundary reflections is addressed and managed experimentally. Pulse excitation is selected as it can excite the structure in a wide frequency range contrary to conventional tone burst excitation. The results show that the proposed non-destructive method can be used in service for estimation of material and geometrical properties of structure in industrial applications.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2012년도 춘계학술발표대회 논문집
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• pp.419-424
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• 2012

This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.565-565
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• 2004

• 한국군사과학기술학회지
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• 제14권4호
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• pp.590-597
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• 2011

The IDRS provides detection, classification and bearing/range estimation by performing wavefront curvature analysis on an intercepted active transmission from target. Especially, a estimate of the target bearing/range that significantly affects the optimal operation of own submarine is required. Target bearing/range can be estimated by wavefront curvature ranging which use the difference of time arrival at sensors. But estimation ambiguity occur in bearing/range estimation due to a number of peaks caused by high center frequency and limited bandwidth of the intercepted active transmission and distortion caused by noise. As a result the bearing/range estimation performance is degraded. To estimate target bearing/range correctly, bearing/range estimation method that eliminate estimation ambiguity is required. In this paper, therefore, for wavefront curvature ranging, NLS cost function with curve fitting method is proposed, which provide robust bearing/range estimation performance by eliminating estimation ambiguity. Through simulation the performance of the proposed bearing/range estimation methods are verified.

• 전자공학회논문지C
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• 제34C권11호
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• pp.95-103
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• 1997

A robust center estimation tecnique of n-fold engineering parts is presented, which use self-organizing neural networks with generating and merging learning for training neural units. To estimate the center of the n-fold engineering parts using neural networks, the segmented boundaries of the interested part are approximated to strainght lines, and the temporal estimated centers by thecosine theorem which formed between the approximaged straight line and the reference point, , are indexed as (.sigma.-.theta.) parameteric vecstors. Then the entries of parametric vectors are fed into self-organizing nerual network. Finally, the center of the n-fold part is extracted by mean of generating and merging learning of the neurons. To accelerate the learning process, neural network uses an adaptive learning rate function to the merging process and a self-adjusting activation to generating process. Simulation results show that the centers of n-fold engineering parts are effectively estimated by proposed technique, though not knowing the error distribution of estimated centers and having less information of boundaries.

• 한국음향학회지
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• 제10권1호
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• pp.37-46
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• 1991

지금까지 제안된 피치 수정 앨고리즘들은 남녀노소에 무관하게 폭넓은 피치범위를 검출하기가 어렵다. 조음기관의 물리적 한계성 때문에 피치의 분포도는 일반적으로 중심 피치에 몰려있는 형태가 된다. 이 중심 피치를 본격적인 피치검출 과정에 적용한다면 그 처리과정이 간단해지고 정확도가 개선될 수 있다. 본 논문에서는 스펙트럼 누설현상을 이용하여 중심피치를 정확하게 검출하는 앨고리즘을 제안한다.

• 한국항해항만학회지
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• 제43권1호
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• pp.16-22
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• 2019

본 연구에서는 국내 소형 어선의 재화상태에 따른 중량 및 무게중심 추정식을 제안하였다. 소형 어선에 탑재되는 중량물은 선원, 어구 등의 고정 중량과 연료, 청수, 식량, 미끼, 어획물 등의 가변 중량으로 분류할 수 있다. 다양한 소형 어선들의 중량 데이터를 통계 분석한 후, 각 탑재물의 중량 및 무게중심을 총톤수에 대하여 선형 함수화하였다. 그리고 재화상태를 고려하여 각 가변 중량물에 가중치를 부가하는 방식으로 총 중량 및 무게중심 추정식을 구성하였다. 소형 어선의 길이와 총톤수, 그리고 재화상태 정보만을 활용하여 총 중량 및 무게중심을 상당히 신뢰도 높게 추정할 수 있음을 검증하였다.

• 대한원격탐사학회지
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• 제36권6_2호
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• pp.1537-1549
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• 2020

KOMPSAT-3의 지상해상도는 전정색 밴드: 0.7 m, 다중 스펙트럴 밴드: 2.8 m이며, 관측 폭의 경우 16 km이다. 따라서 관측 폭(16 km) 보다 넓은 지역의 영상을 한 번의 촬영으로 획득할 수 없으며, 관측 폭 단위로 넓은 지역을 겹치게 촬영 한 후에 획득한 영상들을 하나의 영상으로 만들어야 주어야 한다. 이때 필요한 알고리즘을 영상 모자이킹 또는 영상 스티칭이라고 하며, 지도 제작, 국토관리 분야 등에 사용된다. 모자이킹 알고리즘은 일반적으로 (1) 특징점 추출 및 매칭, (2) 복사 평형, (3) 경계선 추정, (4) 영상 블렌딩의 4단계로 이루어져 있다. 본 논문에서는 위성 영상에서 효과적으로 경계선 추정할 수 있는 방법에 대해 연구하였다. 그 결과 기존의 방법에 비하여 더 정확하게 경계선을 추정할 수 있었으며, 모자이킹이 된 영상도 경계선 부분의 이질감이 최소화 되었다.