• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.8
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• pp.889-895
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• 2007

Quantifying dynamic stability is important to assessment of falling risk or functional recovery for leg injured people. Human locomotion is complex and known to exhibit nonlinear dynamical behaviors. The purpose of this study is to quantify major joints of the body using chaos analysis during walking. Time series of the chaotic signals show how gait patterns change over time. The gait experiments were carried out for ten young males walking on a motorized treadmill. Joint motions were captured using eight video cameras, and then three dimensional kinematics of the neck and the upper and lower extremities were computed by KWON 3D motion analysis software. The correlation dimension and the largest Lyapunov exponent were calculated from the time series to quantify stabilities of the joints. This study presents a data set of nonlinear dynamic characteristics for eleven joints engaged in normal level walking.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.93-101
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and control system, which were hitherto based on linear models. Theory of chaos which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end milling process. Then, it will be verified that cutting force is low-dimensional chaos by calculating Lyapunov exponents. Fractal dimension, embedding dimension. And it will be investigated that the relation between characteristic parameter calculated from sensor signal and tool wear.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.437-450
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• 1994

The problem of testing for a change in the parameter of a stochastic process is particularly important in simulation studies. In studies of the steady state characteristics of a simulation model, it is important to identify initialization bias and to evaluate efforts to control this problem. A simulation output have the characteristics of chaotic behavior because of sensitive dependence on initial conditions. For that reason, we will apply Lyapunov exponent for diagnosis of chaotic motion to simulation output analysis. This paper proposes two methods for diagnosis of steady state in simulation output. In order to evaluate the performance and effectiveness of these methods using chaos theory, M/M/I(.inf.) queueing model is used for testing point estimator, average bias.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.459-462
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• 2000

The analysis of distribution line faults is essential to the proper protection of power system. A high impedance fault(HIF) dose not make enough current to cause conventional protective device operating. so it is well hon that undesirable operating conditions and certain types of faults on electric distribution feeders cannot be detected by using conventional protection system. In this paper, we prove that the nature of the high impedance faults is indeed a deterministic chaos, not a random motion Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents detections in order to evaluate the orbital instability peculiar to deterministic chaos dynamically, and fractal dimensions of fault currents which represent geometrical self-similarity are calculated. Wavelet transform analysis is applied the time-scale information to fault signal. Time-scale representation of high impedance faults can detect easily and localize correctly the fault waveform.

• Journal of Power Electronics
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• v.14 no.6
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• pp.1208-1216
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• 2014

Mismatch between switching frequency and circuit parameters often occurs in industrial applications, which would lead to instability phenomena. The bifurcation behavior of $V^2$ controlled buck converter is investigated as the pulse width modulation period is varied. Nonlinear behavior is analyzed based on the monodromy matrix of the system. We observed that the stable period-1 orbit was first transformed to the period-2 bifurcation, which subsequently changed to chaos. The mechanism of the series of period-2 bifurcations shows that the characteristic eigenvalue of the monodromy matrix passes through the unit circle along the negative real axis. Resonant parametric perturbation technique has been applied to prevent the onset of instability. Meanwhile, the extended stability region of the converter is obtained. Simulation and experimental prototypes are built, and the corresponding results verify the theoretical analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.379-388
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• 2000

Previous studies on high impedance faults assumed that the erratic behavior of fault current would be random. In this paper, we prove that the nature of the high impedance faults is indeed a deterministic chaos, not a random motion. Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents in order to evaluate the orbital instability peculiar to deterministic chaos dynamically, and fractal dimensions of fault currents, which represent geometrical self-similarity are calculated. In addition, qualitative analysis such as phase planes, Poincare maps obtained from fault currents indicate that the irregular behavior is described by strange attractor.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.817-821
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and system, which were hitherto based on linear models. Theory of chaos, which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end millingprocess. Then, it will be verified that cutting force is low-dimensional deterministic chaos calculating Lyapunov exponents, Fractal dimension, Embedding dimension. Aen it will be investigated that the relations between characteristic parameter caculated form sensor signal and tool wear.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.811-815
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• 2005

We theoretically studied synchronization of chaotic oscillation in semiconductor lasers with chaotic light injection feed-back induced chaotic light generated from a master semiconductor laser was injected into a solitary slave semiconductor laser. The slave laser subsequently exhibited synchronized chaotic output for a wide parameter range with strong injection and frequency detuning within the injection locking scheme. We also analytically examined chaos synchronization based on a linear stability analysis from the view point of synchronization based on a linear stability analysis from the view point of modulation response of injection locked semiconductor lasers to chaotic light signal.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.197-202
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• 1999

Electric arc furnaces (EAFs) use bulk electrical energy to create heat in metal refining industries. The electric arc process is a main cause of the degradation of the electric power quality such as voltage flicker due to the interaction of the high demand currents of the load with the supply system impedance. The stochastic models have described the aperiodic physical phenomena of EAFs. An alternative approach is to include deterministic chaos in the characterization of the arc currents. In this parer, a chaotic approach to such modeling is described and justified. At the same time, a DLL(Dynamic Link Library) module, which is a FORTRAN interface with TACS (Transient Analysis of Control Systems), is developed to implement the chaotic load model in the Electromagnetic Transients Program (EMTP). The details of the module and the results of tests performed on the module to verify the model and to illustrate its capabilities are presented in this paper.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.614-618
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• 2005

수문시계열 분석과 예측은 대부분 ARMA(AutoRegressive Moving Average) 형태의 선형적인 추계학적인 모형을 이용하였으나 자현현상이 복잡해지고 비선형적인 특성을 가짐에 따라 선형적인 해석은 수문시계열의 분석과 예측에 있어서 많은 오류를 내포하고 있다. 이와 같은 문제를 해결하기 위한 시도로 Chaos이론이란 개념이 사용되기 시작하였으며, 수자원분야에서는 1980년대 후반부터 물수지 방정식 및 강우유출에 대한 카오스적 특성분석 등 많은 연구가 진행되었다. 본 연구에서는 영산강유역의 본류를 대표하는 나주지점을 대상으로 2003년 1월 1일 00시부터 2004년 12월 31일 23시까지 17,544개의 시수위 자료에 대하여 해당 년도의 Rating-Curve식을 적용 환산한 유출량자료에 데한 카오스적 특성을 분석하였다. 카오스적 특성을 분석하기에 앞서 원자료에 대하여 이동평균법과 Savitzky-Golay Filter를 적용하여 잡음을 제거하였으며, 1차원의 단일변량의 자료에 대한 상태공간(Phase Space)의 재건을 통하여 비교검토 하였다. 이러한 일련의 과정을 거친 자료에 대하여 상관차원법을 이용하여 영산강 유역의 나주지점의 시유출량 자료에 대한 카오스적 특성을 분석한 결과 저차원의 수렴으로 카오스 특성을 가졌다.