• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.8
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• pp.817-825
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• 2007

During thirty years, deterministic chaos has moved center stage in many areas of applied mathematics. One important stimulus for this, particularly in the early 1970s, was work on nonlinear aspects of the dynamics of plant and animal populations. There are many situations, at least to a crude first approximation, by a simple first-order difference equation. Past studies have shown that such equations, even though simple and deterministic, can exhibit a surprising array of dynamical behavior, from stable points, to a bifurcating hierarchy of stable cycles, to apparently random fluctuations. But higher-order spectral analyses of such behavior are usually not considered. Higher-order spectra of a signal contain important information that is not present in its power spectrum. So, if we find the spectral pattern and get information from it, it will be able to be used effectively in so many fields. Hence, this paper uses auto bicoherence and bicoherence residue which are sort of bispectrum. Applying these to behavior of logistic difference equation, which is typical chaotic signal, the phenomenon of phase coupling and the appearance of frequency band can be analyzed. Such information means that bispectral analysis is useful to detect nonlinearity of signal.

• Smart Structures and Systems
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• v.20 no.6
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• pp.669-682
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• 2017

The normalised version of bispectrum, the so-called bicoherence, has often proved a reliable method of damage detection on engineering applications. Indeed, higher-order spectral analysis (HOSA) has the advantage of being able to detect non-linearity in the structural dynamic response while being insensitive to ambient vibrations. Skewness in the response may be easily spotted and related to damage conditions, as the majority of common faults and cracks shows bilinear effects. The present study tries to extend the application of HOSA to damage localisation, resorting to a neural network based classification algorithm. In order to validate the approach, a non-linear finite element model of a 4-meters-long cantilever beam has been built. This model could be seen as a first generic concept of more complex structural systems, such as aircraft wings, wind turbine blades, etc. The main aim of the study is to train a Neural Network (NN) able to classify different damage locations, when fed with bispectra. These are computed using the dynamic response of the FE nonlinear model to random noise excitation.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1436-1439
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• 1997

The objective of this paper is to present an efficient and practical approach to the automatic classification of power quality(PQ) disturbances, where and orthogonal polynomial approximation method is emloyed for the detection and localization of PQ disturbances, and a feature vector, newly extracted form the bispectra of the detected signal, is utilized for the automatic rectgnition of the various types of PQ disturbances. To demonstrae the performance and applicabiliyt of the proposed approach, some simulation results are provided.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.138-141
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• 1994

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.04a
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• pp.176-182
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• 1998

청각자극에 의한 쾌/불쾌 감성상태의 특징을 구별하기 위하여 21채널의 측정된 뇌파신호를 이용하였다. 이를 위하여 비선형 분석방법인 바이스펙트럼 분석을 도입하였으며 청각신호에 잘 반응하는 T3, T4채널에 대하여 조사하였다. 쾌한 감성 상태에서는 비슷한 주파수 쌍의 상호작용이 큼을 알 수 있었다.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.5
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• pp.873-887
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• 2015

The springing response of a large blunt ship was considered to be influenced by a second order interaction between the incoming irregular wave and the blunt geometry of the forebody of the ship. Little efforts have been made to simulate this complicated fluid-structure interaction phenomenon under irregular waves considering the second order effect; hence, the above mentioned premise still remains unproven. In this paper, efforts were made to quantify the second order effect between the wave and vibrating flexible ship structure by analyzing the experimental data obtained through the model basin test of the scaled-segmented model of a large blunt ship. To achieve this goal, the measured vertical bending moment and the wave elevation time history were analyzed using a higher order spectral analysis technique, where the quadratic interaction between the excitation and response was captured by the cross bispectrum of two randomly oscillating variables. The nonlinear response of the vibrating hull was expressed in terms of a quadratic Volterra series assuming that the wave excitation is Gaussian. The Volterra series was then orthogonalized using Barrett's procedure to remove the interference between the kernels of different orders. Both the linear and quadratic transfer functions of the given system were then derived based on a Fourier transform of the orthogonalized Volterra series. Finally, the response was decomposed into a linear and quadratic part to determine the contribution of the second order effect using the obtained linear and quadratic transfer functions of the system, combined with the given wave spectrum used in the experiment. The contribution of the second order effect on the springing response of the analyzed ship was almost comparable to the linear one in terms of its peak power near the resonance frequency.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.49-54
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• 2009

A fuzzy weighted mean method on a 2D shape recognition system is introduced in this paper. The bispectrum based on third order cumulant is applied to the contour sequence of each image for the extraction of a feature vector. This bispectral feature vector, which is invariant to shape translation, rotation and scale, represents a 2D planar image. However, to obtain the best performance, it should be considered certain criterion on the calculation of weights for the fuzzy weighted mean method. Therefore, a new method to calculate weights using means by differences of feature values and their variances with the maximum distance from differences of feature values. is developed. In the experiments, the recognition results with fifteen dimensional bispectral feature vectors, which are extracted from 11.808 aircraft images based on eight different styles of reference images, are compared and analyzed.

• Journal of Biomedical Engineering Research
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• v.7 no.2
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• pp.117-118
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• 1986

It is well known that nonlinear propagation characteristics of the wave in the tissue may give very useful information for the medical diagnoisis. In this paper, a new method to detect nonlinear propagation characteristics of the internal vibration in the tissue for the low frequency mechanical vibration by using bispectral analysis is proposed. In the method, low frequency vibration of f0( = 100Hz) is applied on the surface of the object, and the waveform of the internal vibration x (t) is measured from Doppler frequency modulation of silmultaneously transmitted probing ultrasonic waves. Then, the bispectra of the signal x (t) at the frequencies (f0, f0) and (f0, 2f0) are calculated to estimate the nonlinear propagation characteristics as their magnitude ratio, w here since bispectrum is free from the gaussian additive noise we can get the value with high S/N. Basic experimental system is constructed by using 3.0 MHz probing ultrasonic waves and the several experiments are carried out for some phantoms. Results show the superiority of the proposed method to the conventional method using power spectrum and also its usefulness for the tissue characterization.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.104-112
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• 2001

Simply, Nonlinear dynamics theory means the complicated and noise-like phenomena originated form nonlinearity involved in deterministic dynamical system. An almost all the natural signals have nonlinear property. However, there exist few analysis software tool or package for a research and development of applications. We develop nonlinear time series analysis simulator is to provide a common and useful tool for this purpose and to promote research and development of nonlinear dynamics theory. This simulator is consists of the following four modules such as generation module, preprocessing module, analysis module and ICA module. In this paper, we applied to Electroencephalograph (EEG), as it turned out, our simulator is able to analyze nonlinear time series. Besides, we could get the useful results using the various parameters. These results are used to diagnostic the brain diseases.

• Journal of the KSME
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• v.24 no.6
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• pp.446-451
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• 1984

최근 기계구조물로부터 발생되는 소음. 진동의 수준을 평가하고 그 대책을 수립하는데 스펙트 럼분석(spectral analysis)과 상관기술(correlation technique)의 이용도가 점증하고 있다. 전자계 산기에 의한 데이터처리기술의 진보에 따라 불규칙한 입력을 받는 기계구조물의 고유진동수추정 및 진동모우드해석, 많은 소음. 진동원을 갖는 플랜트. 선박. 차량기기등의 발생원검출 및 기여 량파악, 그리고 acoustic emission 및 bispectrum에 의한 기기이상진단기술에 적용함으로써 공 학분야에서 한층 중요한 위치를 점하고 있다. 따라서 본 강좌에서는 먼저 상관해석에 의한 스 펙트럼의 정의에 대해서 기술하고 샘플링이론에 만족하는 시간간격으로 샘플링함으로써 얻어지는 시계열데이타를 Fourier 변환하여 주파수영역에서 계의 특성을 해석하는 원리 및 기여함수에 대해 설명하고자 한다. 그리고 입력원간에 상관이 존재하는 경우에 있어서 소음. 진동원을 검 출하고 기여량을 추정할 수 있는 방법으로서의 다차원스펙트럼해석법에 대해 간단하게 기술하 고자 한다.