• 조명전기설비학회논문지
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• 제28권4호
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• pp.36-41
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• 2014

Most faults that occur on transmission lines are caused by extreme weather with lightning storms in the distance. These are not only prolongs the time of removing and recovering, but also increases economical damages. If faults can be precisely located, maintenance crews can reach them quickly, and remove the faults in time. So, the precise locating of the faulted point on a transmission line is very important to improve the system reliability, and decreases economic damages as an inherent consequence of long term outages. Also, fault location methods are becoming of much importance for utilities and research. In this paper, two single-terminal impedance-based fault location techniques will be investigated to show the reliability and evaluated the performance of reactance and Takagi method by using MATHCAD program simulations.

• 전자공학회논문지B
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• 제32B권6호
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• pp.821-827
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• 1995

This paper presents a process control language for constructing multiloop control system. which include advanced control algorithms. In order to make controller, this language uses function blocks that do specific operations. Then, the total control algorithm is a set of function blocks, of which each block is represented as a function code. The function code is a line of simple ASCII codes denoting function, input, output, parameters. It is possible to use variables as input/output port of any block. Compared with other language using function block concept, the proposed one enables to use advanced control algorithms undefinitely, such as fuzzy, neural network, predictive controller, etc., because vector and matrix variables as input/output can be used freely in this language. To raise flexibility, we put an intermediate level, which is C-language code, between function code and target-dependent operation code.

• 한국군사과학기술학회지
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• 제3권1호
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• pp.76-84
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• 2000

As first step of any acoustic defence system, a attacking target warning system needs to be extremely reliable. This means the system must ensure a high probability of target classification together with a very low false alarm rate. In this paper, a algorithms for underwater target automatic classification is available for use in the passive sonar will be presented. In first, we will describe the precise automatic extraction of frequency lines for the detection of acoustic signatures. Also, a neural network and fuzzy based algorithms for target classification will be described. Thus the performances of these algorithms are very good with a high probability of classification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권6호
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• pp.2132-2143
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• 2015

This paper presents two distance geometry-based algorithms for wireless location in cellular network systems-distance geometry filtering (DGF) and distance geometry constraint (DGC). With time-of-arrival range measurements, the DGF algorithm estimates the mobile station position by selecting a set of measurements with relatively small NLOS (non-line-of-sight) errors, and the DGC algorithm optimizes the measurements first and then estimates the position using those optimized measurements. Simulation results show that the proposed algorithms can mitigate the impact of NLOS errors and effectively improve the accuracy of wireless location.

• 전자공학회논문지CI
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• 제38권5호
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• pp.27-36
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• 2001

본 논문은 온라인 벡터 양자화기 설계에 stochastic relaxation (SR) 개념을 응용함으로써 SR 방법에 기초한 새로운 온라인 학습 알고리즘을 제안한다. 이는 전통적인 Kohonen 학습법 (KLA)이 안고 있는 극소점(local minimum)으로의 수렴 문제를 개선시켜준다. SR 방법의 응용은 simulated annealing (SA) 개념을 사용하느냐 안 하느냐에 따라 둘로 나눌 수 있는데, 이를 구분하기 위해 SA 개념을 이용하는 SR 알고리즘을 LOVQ-SA로, SA 개념을 이용하지 않는 알고리즘을 OLVQ SR로 부르기로 한다. 제안된 방법들은 KLA와 결합되어 있으며 KLA의 특성을 보존하도록 설계되었다. 이는 제안된 방법들의 수렴의 속도 및 안정성을 향상시켜준다. 제안된 방법의 우수성을 입증하기 위하여 Gauss-Markov 신호원과 음성 및 영상 자료에 대한 벡터양자화 실험을 하였으며 실험결과를 통하여 제안된 방법이 KLA 보다 일관되게 우수한 코드북을 생성함을 보인다.

• 전기학회논문지
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• 제58권2호
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• pp.342-348
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• 2009

This paper introduces a novel denoising algorithm for the partial-discharge(PD) signals from power apparatuses. The developed algorithm includes three kinds of specific denoising sub-algorithms. The first sub-algorithm uses the fuzzy logic which classifies the noise types in the magnitude versus phase PD pattern. This sub-algorithm is especially effective in the rejection of the noise with high and constant magnitude. The second one is the method simply removing the pulses in the phase sections below the threshold count in the count versus phase pattern. This method is effective in removing the occasional high level noise pulses. The last denoising sub-algorithm uses the grouping characteristics of PD pulses in the 3D plot of the magnitude versus phase versus cycle. This special technique can remove the periodical noise pulses with varying magnitudes, which are very difficult to be removed by other denoising methods. Each of the sub-algorithm has different characteristic and shows different quality of the noise rejection. On that account, a parameter which numerically expresses the noise possessing degree of signal, is defined and evaluated. Using the parameter and above three sub-algorithms, an adaptive complex noise rejection algorithm for the on-line PD diagnosis system is developed. Proposed algorithm shows good performances in the various real PD signals measured from the power apparatuses in the Korean plants.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.361-367
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• 1998

The main two applications of the Genetic Algorithms(GA) are the optimization and the machine learning. Machine Learning has two objectives that make the complex system learn its environment and produce the proper output of a system. The machine learning using the Genetic Algorithms is called GA machine learning or genetic-based machine learning (GBML). The machine learning is different from the optimization problems in finding the rule set. In optimization problems, the population of GA should converge into the best individual because optimization problems, the population of GA should converge into the best individual because their objective is the production of the individual near the optimal solution. On the contrary, the machine learning systems need to find the set of cooperative rules. There are two methods in GBML, Michigan method and Pittsburgh method. The former is that each rule is expressed with a string, the latter is that the set of rules is coded into a string. Th classifier system of Holland is the representative model of the Michigan method. The classifier systems arrange the strength of classifiers of classifier list using the message list. In this method, the real time process and on-line learning is possible because a set of rule is adjusted on-line. A classifier system has three major components: Performance system, apportionment of credit system, rule discovery system. In this paper, we solve the food search problem with the learning and evolution of an artificial ant using the learning classifier system.

• 대한기계학회논문집B
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• 제27권8호
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• pp.1122-1133
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• 2003

Numerical characteristics of implicit upwind schemes, such as upwind ADI, line Gauss-Seidel (LGS) and point Gauss-Seidel (LU) algorithms, for Navier-Stokes equations have been investigated. Time-derivative preconditioning method was applied for efficient convergence at low Mach/Reynolds number regime as well as at large grid aspect ratios. All the algorithms were expressed in approximate factorization form and von Neumann stability analysis was performed to identify stability characteristics of the above algorithms in the presence of high grid aspect ratios. Stability analysis showed that for high aspect ratio computations, the ADI and LGS algorithms showed efficient damping effect up to moderate aspect ratio if we adopt viscous preconditioning based on min-CFL/max-VNN time-step definition. The LU algorithm, on the other hand, showed serious deterioration in stability characteristics as the grid aspect ratio increases. Computations for several practical applications also verified these results.

• 한국통신학회논문지
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• 제14권5호
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• pp.486-502
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• 1989

본 논문에서는 로보트 매니퓰레이터의 정밀한 경로 제어를 위해서, 두가지 형태의 로보트 관절 각도 및 관절 속도의 예측 알고리즘을 제시하고, 이를 이용한 제어 방법을 기술하고자 한다. 구체적으로, 로보트 메니퓰레이터의 동특성을 Computed torque방법으로 선형화 시킨후에, 선형화된 모델을 근거로 한 이산시간 상태변수 예측기를 제안한다. 또한, 현재의 관절 위치 및 관절 속도와 과거 및 개의 위치 및 속도 등을 최소 자승법의 의미로 가장 잘 부합시키는 직선을 찾고, 그 직선으로부터 상태를 예측하는 예측기를 제안한다. 이 후에 이들 두 예측기로부터 정보를 이용하여, 예측된 궤적과 원하는 궤적 사이의오차에 적절한 이득을 곱해서 입력 토오크에 보정되어 사용됨으로써 궤적 오차를 줄일 수 있음을, 2자유도를 갖는 SCARA 로보트를 대상으로 컴퓨터 모의 실험을 통하여 보이고자 한다.

• 대한전기학회논문지:전력기술부문A
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• 제51권9호
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• pp.467-473
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• 2002

In this paper, a fault location algorithm is suggested for line to line faults in distribution networks. Conventional fault location algorithms use the symmetrical component transformation, a very useful tool for transmission network analysis. However, its application is restricted to balanced network only. Distribution networks are, in general, operated in unbalanced manners, therefore, conventional methods cannot be applied directly, which is the reason why there are few research results on fault location in distribution networks. Especially, the line to line fault is considered as a more difficult subject. The proposed algorithm uses direct 3-phase circuit analysis, which means it can be applied not only to balanced networks but also to unbalanced networks like distribution a network. The comparisons of simulation results between one of conventional methods and the suggested method are presented to show its effectiveness and accuracy.