• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2006년도 추계학술대회논문집
• /
• pp.591-596
• /
• 2006

This study is base on the fault detection and diagnosis when a crack is happened a structure. A crack in a structure will affect the modal parameters. We are searched a percentage of changes in the natural frequencies according to changes of location and propagation of the crack using the Rayleigh's energy method. This method is presented to identify the presence of a crack and its location. The study is carried out both theoretically and experimentally and the results are presented in this paper. The location of the crack is also moved from the fixed end to the free end along its length. The changes in natural frequencies are observed from theoretically study, due to the presence of the crack at different locations and depths, and the percentage change in frequency values are calculated. These results are confirmed by the experiments. And then, a difference between a cracked beam and uncracked beam observed using the bispectrum as high-order spectrum.

• 한국멀티미디어학회논문지
• /
• 제3권3호
• /
• pp.241-252
• /
• 2000

이 논문에서는 2차원 영상의 외곽선 정보를 이용하여 추출한 바이스펙트럼과 가중치 퍼지 분류기를 이용하여 영상의 이동, 회전, 크기 변화에 무관한 패턴 인식 기법을 제안하고, 그 인식 결과를 LVQ(Learning Vector Quantization)를 이용한 신경망 분류기와 비교하였다. 3차 큐물런트를 근간으로하는 바이 스펙트럼은 각 영상의 외각선 정보에 적용되어 15개의 특징값들을 추출한다. 이 특징 벡터들은 영상의 이동, 회전, 크기 변화에 무관한 특징을 가지며 2차원 평면 영상의 대표값으로 사용되어 패턴 분류를 위해 가중치 퍼지 분류기의 입력으로 들어간다. 서로 다른 8가지 비행기들의 평면 영상을 이용하여 실험한 결과들은 제안된 인식 시스템의 성능이 상대적으로 우수함을 보였다.

• 한국음향학회지
• /
• 제11권1호
• /
• pp.5-13
• /
• 1992

어느 신호의 특성을 주파수 영역에서 해석할 때, 파워스펙트럼은 해석하고자 하는 신호의 위상에 관한 정보를 모두 잃어 버리는 단점이 있어서, 위상에 관한 정보를 필요로 하는 경우에는 파워스펙트럼 해석법은 그 이용에 제한을 받는다. 고차스펙트럼(특히 본 논문에서는 3차 스펙트럼인 바이스펙트럼)은 그 계산에 시간이 많이 걸리는 단점은 있으나 반면에 위상에 관한 정보를 잃지 않는다는 장점이 있다. 본 논문에서는 몇가지 이상적인 경우에 대한 바이스펙트럼의 예를 보이고, 실제로 노상에서 녹음된 자동차들의 엔진 소음에 대한 바이스펙트럼을 구한후, 이를 이용하여 음향 식별을 할 수 있음을 보였다.

• 한국정보처리학회논문지
• /
• 제6권5호
• /
• pp.1312-1322
• /
• 1999

The world of linearity, which is regular, predictable and irrelevant to time sequence in most natural phenomenon, is a very small part. In fact, signals generated from natural phenomenon with which we're in contact are showed only slight linearity. Therefore it is very difficult to understand and analyze natural phenomenon with only predictable and regular linear systems. Due to these reasons researches concerning non-linear signals that of analysis were excluded being regarded as noise are being actively carried out. Countless signals generated from nonlinear system have the information about itself, and analyzing those signals and get information from it, that will be able to be used effectively in so may fields. Hence, in this paper we used a higher order spectrum, especially the bispectrum. After we prove the validity applying bispectrum to logistic map, which is typical chaotic signal. Subsequently by showing the result applying for actual signal analysis of EEG according to auditory stimuli, we show that higher order spectra is a very useful parameter in analysis of non-linear signals and the result of EEG analysis according to auditory stimuli.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
• /
• pp.313-320
• /
• 1999

In this paper, a translation, rotation and scale invariant system for the classification of closed 2D images using the bispectrum of a contour sequence and the weighted fuzzy mean method is derived and compared with the classification process using one of the competitive neural algorithm, called a LVQ(Learning Vector Quantization). The bispectrun based on third order cumulants is applied to the contour sequences of the images to extract fifteen feature vectors for each planar image. These bispectral feature vectors, which are invariant to shape translation, rotation and scale transformation, can be used to represent two-dimensional planar images and are fed into an classifier using weighted fuzzy mean method. The experimental processes with eight different shapes of aircraft images are presented to illustrate the high performance of the proposed classifier.

• 한국자동차공학회논문집
• /
• 제8권4호
• /
• pp.85-92
• /
• 2000

The pulsating pressure waves are composed of fundamental frequency and higher order harmonics in exhaust pipe of engines. The nonlinearity in exhaust pipe is caused by their interactions. The error which is between prediction and measurement is induced by the nonlinearity. We can not explain this phenomenon using linear acoustic theory which is existing theory. So power spectrum which was used in linear theory is not useful. Bispectrum and bicoherence functions which are a higher order spectrum are applicable to explain this phenomenon. This paper proposes a nonlinear effect of pulsating pressure waves. The phenomenon proposed here is identified by using of higher order spectrum density functions.

• 한국감성과학회:학술대회논문집
• /
• 한국감성과학회 2003년도 춘계학술대회 논문집
• /
• pp.115-119
• /
• 2003

본 연구는 인간에 있어서 가장 간단한 의사라고 여겨지는 긍정과 부정 응답에 대해 나타나는 뇌파의 변화를 잘 반영하는 특징을 찾아내고자 하기 위한 것이다. 고차 통계적 방법(high order statical analysis)인 바이스펙트럼(bispectrum)은 뇌파의 다른 부위와 다른 주파수 사이의 비선형위상커플링(non-linear phase coupling)을 잘 반영하므로, 이를 이용하여 긍정이나 부정을 선택할 때 나타나는 뇌파를 분석하였다. 분석결과, 반응 전 1.25초∼0.5초 에 유의미한 차이를 보였다. 긍정과 부정 응답에 대한 뇌파의 주파수와 부위를 찾아 신경회로망의 입력으로 사용하여 긍정과 부정 응답에 대해 분별하였다. 2번의 뇌파실험에서 각각 실험 데이터에 대해서는 긍/부정 차이가 존재하지만 공통적인 특징이 나타나지는 않았다.

• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1994년도 추계학술대회
• /
• pp.124-127
• /
• 1994

A technique based on bispectrun averaging is described for generally recovering the signal waveform from a set of noisy signals with variable signal delay. The technique does not require explicit tune alignment of signals and any initial estimate of signal. The new method is suggested and is compared with other methods. This method are numerically investigated using computer generated-data and a physiological signal and noise Some experimental results for the evoked potential studios that demonstrate the technique are given. The results show the effectiveness of the technique: various potential applications of the technique might be expected.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
• /
• pp.255-262
• /
• 1998

This paper presents a translation, rotation and scale invariant methodology for the recognition of closed planar shape images using the bispectrum of a contour sequence and the learning vector quantization(LVQ) neural classifier. The contour sequences obtained from the closed planar images represent the Euclidean distance between the centroid and all boundary pixels of the shape, and are related to the overall shape of the images. The higher order spectra based on third order cumulants is applied to tihs contour sample to extract fifteen bispectral feature vectors for each planar image. There feature vector, which are invariant to shape translation, rotation and scale transformation, can be used to represent two0dimensional planar images and are fed into a neural network classifier. The LVQ architecture is chosen as a neural classifier because the network is easy and fast to train, the structure is relatively simple. The experimental recognition processes with eight different hapes of aircraft images are presented to illustrate the high performance of this proposed method even the target images are significantly corrupted by noise.

• 국제학술발표논문집
• /
• The 6th International Conference on Construction Engineering and Project Management
• /
• pp.179-182
• /
• 2015

Detecting and assessing human-related risks is critical to improve the on-site safety condition and reduce the loss in lives, time and budget for construction industry. Recent research in neural science and psychology suggest inattentional blindness that caused by overload in working memory is the major cause of unexpected human related accidents. Due to the limitation of human mental workload, laborers are vulnerable to unexpected hazards while focusing on complicated and dangerous construction tasks. Therefore, detecting the risk perception abilities of workers could help to identify vulnerable individuals and reduce unexpected injuries. However, there are no available measurement approaches or devices capable of monitoring construction workers' mental conditions. The research proposed in this paper aims to develop such a measurement framework to evaluate hazards through monitoring electroencephalogram of labors. The research team developed a wearable safety monitoring helmet, which can collect the brain waves of users for analysis. A bispectrum approach has been developed in this paper to enrich the data source and improve accuracy.