• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.161-164
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• 1995

Nonlinear analysis of various phenomena has been developed with improvement of computer. The characteristics form nonlinear analysis are available in monitoring and diagnosis state of system. There are many nonlinear property in cutting process, but nonlinear signals have been considered as noise. In this study, nonlinear analysis technique is applied and it will be verified that cutting force is chaos by calculating Lyapunov exponents,fractal dimension and embedding dimension. The relation between characteristic parameter calculated form sensor signal and various cutting condition is investigated.

• 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 KSME
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• v.31 no.6
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• pp.540-550
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• 1991

chaos이론은 현재 사회과학과 자연과학의 많은 분야에 있어서 연구 수단 또는 연구 대상으로서의 폭발적인 인기를 누리고 있다. 열 . 유체역학, 동력학, 구조역학, 화학(화학 분야에 있어서의 chaos개념은 Prigogine(1978년Nobel상 수상자)과 Stengers의 저서에 잘 기술되어 있음), 플라즈마 물리학, 전자공학, 전기공학 등 우리들에게 친숙한 학문은 말할 것 없고, 의학, 생태학, 생물학, 인구학, 경제학, 회계학 등에서도 종래의 것과는 완전히 다른 시각에서 현상을 분석하고 예측하 려는 노력을 하고 있다. 그리고 최근에는 computer graphics 에서도 간단한 수식 모델로 fractal set를 형성시켜, 각종 나무, 꽃, 파도, 구름등 자연의 산물들을 성공적으로 묘사하고 있다. Gleick는 chaos이론에 의한 각 분야에 있어서의 새로운 현상을 Newton-Einstein 이후의 또 다른 과학 혁명이라 부르고 있다. 그리고, 지금까지의 서양 학문이 줄곧 세부화의 길을 달려 왔으나 chaos에 의해 그 과정이 역으로 될 것이라는 인식이 일고 있다. 이는 chaos의 질서의 법칙이 보편타당성(universality)의 일면을 갖고 있다는데 기인되며, 종합화를 지향하는 동양의 제반 학 문과 그 성격상 일맥상통한 점이 있어, chaos학이 동양인의 기호 학문이 되리라 믿는다.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.45-51
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• 2000

This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.

• Journal of Welding and Joining
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• v.16 no.6
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• pp.86-96
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• 1998

This study proposes the analysis method of time series ultrasonic signal using the chaotic feature extraction for degradation extent evaluation. Features extracted from time series data using the chaotic time series signal analyze quantitatively degradation extent. For this purpose, analysis objective in this study is fractal dimension, lyapunov exponent, strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal correlation) dimensions, lyapunov exponents, energy variation showed values of 2.217∼2.411, 0.097∼ 0.146, 1.601∼1.476 voltage according to degardation extent. The proposed chaotic feature extraction in this study can enhances precision ate of degradation extent evaluation from degradation extent results of the degraded materials (SA508 CL.3)

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.57
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• pp.51-62
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• 2000

In this study, the psycho-physiological response of drivers was investigated in terms of EEG(Electroencephalogram), especially with the fractal dimensions computed by Chaotic algorithm. The Chaotic algorithm Is well Known to sensitively analyze the non-linear information such as brain waves. An automobile with a fully equipped data acquisition system was used to collect the data. Ten healthy subjects participated in the experiment. EEG data were collected while subjects were driving the car between Won-ju and Shin-gal J.C. on Young-Dong highway The results were presented in terms of 3-Dimensional attractor to confirm the chaotic nature of the EEG data. The correlation dimension and fractal dimension were calculated to evaluate the complexity of the brain activity as the driving duration changes. In particular, the fractal dimension indicated a difference between the driving condition and non-driving condition while other spectral variables showed inconsistent results. Based upon the fractal dimension, drivers processed the most information at the beginning of the highway driving and the amount of brain activity gradually decreased and stabilized. No particular decrease of brain activity was observed even after 100 km driving. Considering the sensitivity and consistency of the analysis by Chaotic algorithm, the fractal dimension can be a useful parameter to evaluate the psycho-physiological responses of human brain at various driving conditions.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2525-2527
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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 known 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.113-119
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• 2013

In this paper, n order to degrade of diagnosis of power supply by using Poincare map and fractal dimension with temperature measured by infrared camera. we review the characteristic of temperature variation according to pattern variation of power supply in chemical industry complex. As a simulation results we can be realized the characteristic behaviors of nonlinear dynamics in the poincare mal and fractal dimension. In the future verification method requires through additional research.

• KIEE International Transactions on Electrophysics and Applications
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• v.11C no.2
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• pp.6-11
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• 2001

Abstract- In this paper, a new Partial Discharge (PD) detection using Pockels cell was proposed and considerable apparent chaotic characteristics were discussed. For this purpose, PD was generated from needle-plane electrode in air and detecte by optical measuring system using Pockels cell, based on Mach-Zehner interferometer, consisting of He-Ne laser, single mode optical fiber, 50/50 beam splitter and photo detector. In addition, the presence of chaos of the PD signals has been investigated by examining their means of qualitative and quantitative information. For the former, return map and 3-dimensional strange attractor have been drawn in order to investigate the presence of chaotic characteristics relevant to PD signals, detected through CT and Peckels sensor respectively, in the normalized time series. The presence of strange attractor indicates the existence of fractal structures in it's phase space. For the latter, several dimension values of strange attractor were verified sequentially. Throughout this paper, it is likely that the chaotic characteristics regarding the PD signals under air are verified.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.11 no.2
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• pp.84-95
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• 2007

Background and Purpose: We have studied the trends of EEG signals in the voluntary breathing condition by applying the fractal analysis. According to chaos theory, irregularity of EEG signals can result from low dimensional deterministic chaos. A principal parameter to quantify the degree of Chaotic nonlinear dynamics is correlation dimension. The aim of this study was to analyze correlation between the correlation dimension of EEG and HRV(heart rate variability). We have studied the trends of EEG signals in the voluntary breathing condition by applying the fractal analysis. Methods: EEG raw data were measured by moving windows during 15 minutes. Then, the correlation dimension(D2) was calculated by each 40-seconds-segment in 15 minutes data, totally 36 segments. 8 channels EEG study on the Fp, F, T, P was carried out in 30 subjects. Results and Conclusion: Correlation analysis of HRV was calculated with deterministic non-linear data and stochastic non-linear data. 1. Ch1(Fp1), Ch4(F3), Ch4(F4) is positive correlated with In LF. 2. Ch1(Fp1), Ch3(F3) is positive correlated with In TF.