• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.128-133
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• 1986

설비진단에 응용되는 신호처리의 기법으로는 파워스펙트럼, 바이스펙트럼, 켑스트럼 등이 사용되었다. 파워스펙트럼은 이론적인 면과 계산과정 그리고 신호처리에서의 적용방법등이 잘 알려져서 성공적으로 사용되어져 왔다. 특히 음향분야에서는 여러가지 응용기술이 개발되어 실제계에 적용되고 있으며 계측장비도 파워스펙트럼 해석법에 알맞게 개발되어져 왔다. 파워스펙트럼해석법을 사용하여 진동계를 구성하는 각 요소들의 고유진동수와 진동계 전체를 나타내는 진동파들의 주파수성분 간의 관계에 의하여 진동의 원인 및 소음원 등을 추정하는 것이 가능하다. 그러나 파워스펙트럼은 일반적으로 정상적인 신호를 갖는 진동계에 대한 해석 일 때는 그 이론과 실제가 잘 일치하지만, 진동계 자체가 항시 임의의 주파수를 갖고서 움직일 때 그 해석에는 다음과 같은 문제점이 생긴다. 첫째, 불규칙한 진동계에서는 규칙적인 진동계보다 잡음의 영향을 많이 받기 때문에 실제로 잡음이 진동계의 고유주파수 부근에 있을 경우에는 파워스펙트럼해석으로는 불가능한 경우가 있다. 둘째, 진동파 중에 포함되어 있는 위상이라는 중요한 정보가 없다. 셋째, 시간지연에 따른 진동계의 정확한 정보를 얻을 수 없다. 이상에서 볼 때 파워스펙트럼해석법은 한계가 있음을 알 수 있다. 따라서 본 논문은 바이스펙트럼이라는 해석법을 사용하여 정상과정에서 비정상과정으로 시간지연에따라 변하는 진동계 또는 정상적인 진동계의 저주파에서의 상호간섭 정도 및 위상관계를 관찰함으로써 파워스펙트럼과 비교하여 바이스펙트럼해석법의 타당성을 검토한다. 바이스펙트럼의 실제적인 계산방법은 P. J. Huber가 세가지 접근 방법을 제안했는데 시간영역에서의 평균화를 행하여 계산하는 법, 연속된 기록들을 평균화하는 것, 주파수 영역에서의 평균화를 행하는 것 등이 있다. 본 논문에서는 FFT를 먼저 행하고 파워스펙트럼과 바이스펙트럼 및 바이코히어런스를 구하였다. 그러나 바이스펙트럼해석법은 수치해석적인 면에서 볼 때 파워스펙트럼해석법에 비하여 미약한 점이 많고 통계학적인 그 의미가 확실하게 알려져 있지 않기 때문에 본 논문에서는 시뮬레이션을 통하여 그 물리적 의미를 규명하고져 한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.98-109
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• 2000

While the bispectrum has desirable properties in itself and therefore has a lot of potential to be applied to signal and Image restoration. few real-world application results have appeared in literature The major problem with this IS the difficulty In realizing the expectation operator of the true bispectrum, due to the lack of realizations. In this paper, the true bispectrum is defined as the expectation of the sample bispectrum, which IS the Fourier representation of the triple correlation given one realization The characteristics of the sample bispectrum are analyzed and a way to obtain an estimate of the true bispectrum without stochastic expectation, using the generalized theory of weighted regularization is shown. The bispectrum estimated by the proposed algorithm is experimentally demonstrated to be useful for signal recovery under blurred noisy condition.

• The Journal of the Acoustical Society of Korea
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• v.11 no.1
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• pp.5-13
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• 1992

Since power spectrum has no information about the phase of a signal, the power spectral analysis technique can not be used to interpret the phase coherency of the signal produced by some nonlinear process. In this case, third-order spectrum, the so called bispectrum, is very useful in analyzing such signals. some typical computer simulation results are shown in order to represent the usefulness of the bispectrum, and the bispectra of the measured acoustic signals of three vehicles are shown in order to use to identify the sources of those signals.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1471-1476
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• 2015

Due to the anesthesia process is inappropriate on the operation, awakening state was appeared. To prevent the state, it is necessary to monitor the patients by measuring the depth of anesthesia. In this study, we investigate the possibility of the development of actual surgery available quantitative indicators. The DFA which is included the correlation property of the EEG is used to analysis the depth of anesthesia and bispctrum index. In the results, at the pre-operation, the peak of bispectrum was widely distributed, DFA value was decreased. At the during operation, bispectrum was concentrically appeared in the low frequency area. At the post operation, bispectrum and DFA was both returned to the pre-operation state. We confirmed to be close correlation between the peaks of the bispectrum and DFA value.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.63-69
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• 2019

In this study, bispectrum analysis method introduced to reduce variability of SEF(spectral edge frequency) and MF(median frequency), which are the anesthetic depth indexes extracted by EEG spectral analysis. Bispectrum analysis is an analytical method that can confirm the nonlinearity of EEG. Signal measurement and analysis in the surgical environment should take into consideration various external artifact factors. Bispectrum analysis can confirm the presence of externally introduced artifacts, thereby effectively eliminating artifacts that affect the EEG signal. By applying bispectrum parameters, real-time variability of the anesthetic depth parameters SEF, MF could be reduced. Elimination of variability makes it possible to use SEF, MF as a real-time index during surgery.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.397-400
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• 2015

Due to the anesthesia process is inappropriate on the operation, awakening state was appeared. Because of that patients suffered from severe mental and physical pain. To prevent the state, it is necessary to monitor the patients by measuring the depth of anesthesia. In this study, we investigate the possibility of the development of actual surgery available quantitative indicators. The DFA(detrended fluctuation analysis) which is included the correlation property of the EEG is used to analysis the depth of anesthesia and bispctrum index. In the results, at the pre-operation, the peak of bispectrum was widely distributed, DFA value was decreased. At the during operation, bispectrum was concentrically appeared in the low frequency area. At the post operation, bispectrum and DFA was both returned to the pre-operation state. As a result, we confirmed to be close correlation between the peaks of the bispectrum and DFA value.

• The Journal of the Acoustical Society of Korea
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• v.14 no.2E
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• pp.19-24
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• 1995

The maximum entropy method is a well-known parametric estimation method of the power spectrum with high-resolution for short-time signals. Although a parametric estimation method for the bispectrum was proposed in recent years, it is not easy to estimate the bispectrum with high resolution for relatively short-time signals of which the total length is about 1000 data points. In this paper, a bispectrum estimation method is proposed to estimate the high-resolution bispectrum even for the relatively short-time signals.

• Journal of Navigation and Port Research
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• v.41 no.1
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• pp.1-8
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• 2017

The estimation of non-linear ship motion is one of the most important issues in recent studies of ship stability. In this paper, bispectral analysis and bicoherence analysis were introduced in order to analyze the non-linear ship motion. In addition to the previously observed non-linear pitching motion in following seas, this study observed the non-linear phase coupling of pitching motion in following & quartering seas, and starboard beam seas. By comparing phase coupling between each frequency quantitatively via the bicoherence analysis, it was confirmed that non-linear phase coupling was much stronger in frequency regions other than the peak frequencies of a power spectrum. Furthermore, it was found out that the results of bicoherence calculation were analagous to each other, although the different normalization methods were applied.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.278-285
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• 1999

This paper is concerned with the development of useful engineering techniques to detect and anlayse nonlinearities in mechanical systems. The methods developed are based on the concepts of higher order spectra. The study of higher order statistics has been dominated by work on the bispectrum. The bispectrum can be viewed as a decomposition of the third moment(skewness) of a quadratic phase coupling(QPC) can be analyzed by bicoherence function. Finally, the application of these techiques to data from actual mechanical systems will be performed insecond report.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.2
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• pp.85-92
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• 1999

The fact that material degradation can be evaluated by measuring nonlinear acoustic effect has been proposed by previous studies. The most conventional method to measure nonlinear acoustic effect is to measure the absolute magnitude of fundamental and $2^{nd}$ order harmonic frequency component in the propagated ultrasonic wave. For this aim, power spectral analysis technique has been used widely. However, the power spectral analysis has fatal disadvantage that the gaussian additive noise superimposed in the wave signal remains in the power spectrum domain. Moreover, the magnitude of $2^{nd}$ order harmonic frequency component generated by nonlinear effect is so small that it may be suppressed by the noise remained in the power spectrum. In order to overcome this problem, this paper proposes an alternative method using bispectrum analysis, which can reduce the effect of addictive gaussian noise and. the nonlinear parameter can be obtained more stably. Simulations showed that the proposed method can obtain the value of nonlinear parameter near to the true value in the case of low SNR signal. Also, in order to confirm the usefulness of our method in actual case, we compared the nonlinear parameter obtained by using both of power spectral and bispectral analysis for several specimen intentionally degraded by fatigue load.