• 신재생에너지
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• 제20권2호
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• pp.2-16
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• 2024

Various loads induced by marine environmental conditions, such as waves, currents, and wind, are crucial for the operation and viability of offshore wind power (OWP) systems. In particular, waves have a significant impact on the stress and fatigue load of offshore structures, and highly reliable design parameters should be derived through extreme value analysis (EVA) techniques. In this study, extreme wave analyses were conducted with various Weibull distribution models to determine the reliable design parameters of an OWP system suitable for the Ulsan area. Forty-three years of long-term hindcast data generated by a numerical wave model were adopted as the analyses data, and the least-squares method was used to estimate the parameters of the distribution function for EVA. The inverse first-order reliability method was employed as the EVA technique. The obtained results were compared among themselves under the assumption that the marginal probability distributions were 2p, 3p, and exponentiated Weibull distributions.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2003년도 춘계전력전자학술대회 논문집(1)
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• pp.54-57
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• 2003

A new non linear, mean value, instantaneous following control technique to design half bridge converter is proposed in witch control principle uses characteristic that reset time of analog integrator is inverse proportion In input voltage. It is Important characteristic that compensation and follow-up control time are same with switching frequency. Is completed in one cycle that base control frequency. Have excellence characteristic that follow in order instruction value exactly stationary state as well as transient state. Half bridge converter that apply this control principle can know that have stabilize and excellence characteristic. This technique is verified through an experiment, and know that experiment result and theory agree well.

• Journal of Magnetics
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• 제21권2호
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• pp.197-203
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• 2016

A naval ship equipped with a degaussing system may undergo a breakdown in degaussing coils at sea. In the case, underwater magnetic field around the ship abruptly grows up and it can make the ship be easily exposed to fatal hazards such as magnetic mines or torpedoes. This paper proposes an efficient and practical re-degaussing technique for a ship where a part of degaussing coils is out of order. To achieve this, an analytical design sensitivity formula and approximated degaussing coil field are exploited, and then new optimum currents of available coils are reassessed. To validate the proposed method, a muck-up ship equipped with 14 degaussing coils is tested in scale-down magnetic treatment facilities under three faulty coil conditions.

• 대한기계학회논문집
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• 제12권4호
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• pp.730-737
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• 1988

본 연구에서는 로봇 매니퓰레이터의 각 조인트 토오크를 구하고, 이를 최소자 승법에 의하여 각 링크의 길이를 최적화하였다. 이때 각 링크의 단면은 일정하며 따 라서 각 링크의 무게중심은 링크의 중앙에 있다고 보았다. 작업은 직선운동(C.P)으 로 하였고 이때의 소고 선도를 편의상 삼각형으로 하였다. 작업시간은 속도선도와 작업경로가 주어지면 구하여지고, 이를 등간격으로 나누어 매 순간마다의 조인트 토오 크를 구하였다. 이때 매 순간 기구학적 해석으로 조인트의 변위, 속도, 가속도를 구 하고 Newton-Euler 운동방정식을 이용하여 각 조인트 토오크를 구하였다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
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• pp.787-796
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• 1995

A man model is a useful design tool for the evaluation of man machine systems and products. An arm reach trajectory prediction for such a model will be specifically useful to present human activities and, consequently, could increase the accuracy and reality of the evaluation. In this study, a three-dimensional reach trajectory prediction model was developed using an inverse kinematics technique. The upper body was modeled as a four link open kinematic chain with seven degrees of freedom. The Resolved Motion Method used for the robot kinematics problem was used to predict the joint movements. The cost function of the perceived discomfort developed using the central composite design was also used as a performance function. This model predicts the posture by moving the joints to minimize the discomfort on the constraint of the end effector velocity directed to a target point. The results of the pairwise t-test showed that all the joint coordinates except the shoulder joint's showed statistically no differences at .alpha. = 0.01. The reach trajectory prediction model developed in this study was found to accurately simulate human arm reach trajectory and the model will help understand the human arm reach movement.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.81-84
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• 1996

We propose the robust nonlinear controller design methodology, the $H_{\infty}$ constrained quasi - linear quadratic Gaussian control (QLQG/ $H_{\infty}$), for the statistically-linearized multivariable system with hard nonlinearties such as Coulomb friction, deadzone, etc. The $H_{\infty}$ performance constraint is involved in the optimization process by replacing the covariance Lyapunov equation with the Riccati equation whose solution leads to an upper bound of the QLQG performance. Because of the system's nonlinearity, however, one equation among three Riccati equations contain the nonlinear correction terms that are very difficult to solve numerically. To treat this problem, we use simple algebraic techniques. With some analytic transformation for Riccati equations, the nonlinear correction terms can be so eliminated that the set of a linear controller to the different operating points are designed. Synthesizing these via inverse random input describing function (IRIDF) technique, the final nonlinear controller can be designed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.371-372
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• 2007

In this paper we present performance and implementation comparisons of high performance two dimensional forward and inverse Discrete Cosine Transform (2D-DCT/IDCT) algorithm and low power algorithm for $8{\times}8$ 20 DCT and quantization based on partial sum and its corresponding hardware architecture for FPGA in MPEG-4. The architecture used in both low power 20 DCT and 2D IDCT is based on the conventional row-column decomposition method. The use of Fast algorithm and distributed arithmetic(DA) technique to implement the DCT/IDCT reduces the hardware complexity. The design was made using Mentor Graphics Tools for design entry and implementation. Mentor Graphics ModelSim SE6.1f was used for Verilog HDL entry, behavioral Simulation and Synthesis. The 2D DCT/IDCT consumes only 50% of the Operating Power.

• Smart Structures and Systems
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• 제8권4호
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• pp.343-365
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• 2011

Structural system identification (SSI) is an inverse problem of difficult solution. Currently, difficulties lie in the development of algorithms which can cater to large size problems. In this paper, a parameter estimation technique based on evolutionary strategy is presented to overcome some of the difficulties encountered in using the traditional system identification methods in terms of convergence. In this paper, a non-traditional form of system identification technique employing evolutionary algorithms is proposed. In order to improve the convergence characteristics, it is proposed to employ immune algorithms which are proved to be built with superior diversification mechanism than the conventional evolutionary algorithms and are being used for several practical complex optimisation problems. In order to reduce the number of design variables, domain decomposition methods are used, where the identification process of the entire structure is carried out in multiple stages rather than in single step. The domain decomposition based methods also help in limiting the number of sensors to be employed during dynamic testing of the structure to be identified, as the process of system identification is carried out in multiple stages. A fifteen storey framed structure, truss bridge and 40 m tall microwave tower are considered as a numerical examples to demonstrate the effectiveness of the domain decomposition based structural system identification technique using immune algorithm.

• 대한토목학회논문집
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• 제10권2호
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• pp.67-78
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• 1990

본 연구에서는 합리적이고 과학적인 포장 구조체의 유지 관리를 위하여 포장체의 구조적 상태를 평가하는데 중요하게 사용되는 포장체 각 층의 탄성계수 추정 방법에 대하여 연구하였다. 차량하중에 의한 포장체의 구조적 거동을 측정하는 비파괴시험 방법으로 Falling Weight Deflectometer(FWD)를 택하였으며, 측정 결과를 합리적으로 해석하기 위하여 다층탄성이론에 근거한 해석 프로그램을 사용하였다. 국내에서 널리 사용되고 있는 고속도로 단면 모델에 요인배치법(factorial design)을 적용하여 쇄석과 안정처리기층을 갖는 경우 각각에 대한 이론적 처짐특성을 분석하고, 이로부터 각 경우의 층별 탄성계수 추정식을 제안하였다. 처짐 변화율에 따른 탄성계수 변화율에 과한 상관식을 4층 구조체 층별로 개발함으로써 FWD시험의 처짐으로부터 포장체 각 층의 탄성계수를 추정할 수 있는 보다 효율적이며 정도가 높은 역산방법을 제안하고 이를 전산화하였다. 또한 4층 아스팔트 포장체의 실제 가능한 수치 모델에 대한 검증을 통하여 본 연구에서 제안한 역산 방법의 신뢰성 및 타당성을 입증하였다.

• 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.