• 소음진동
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• 제7권4호
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• pp.637-644
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• 1997

In this paper, a method of finite element analysis is presented for efficient calculation of vibration characteristics of not only simply interconnected structure with cyclic symmetry but also multiply interconnected structure with cyclic symmetry by using discrete Fourier trandform by means of a computer with small memory in a short time. Simply interconnected structure means it is composed of substructures which are adjacent themselves in circumferential direction. First, a mathematical model of multiply interconnected structure with cyclic symmetry is defined. The multiply interconnected structure is partitioned into substructures with the same goemetric configuration and constraint eqauations to be satisfied on connecting boundaries are defined. Nodal displacements and forces are transformed into complex forms through discrete Fourier transform and then finite element analysis is performed for just only a representative substructure. In free vibration analysis, natural frequencies of a whole structure can be obtained through a series of calculation for a substructure along the number of nodal diameter. And in forced vibration analysis, forced response of whole structure can be achieved by using inverse discrete Fourier transform of results which come from analysis for a substructure.

• 한국소음진동공학회논문집
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• 제16권6호
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• pp.627-633
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• 2006

The tire is considered as one of the important noise sources having an influence on vehicle's performance. The Pattern noise of a tire is the transmission sound of airborne noise. On smooth asphalt road, Pattern noise is amplified with the velocity. In recent, the study on the reduction of Pattern noise is energetically processed. Pattern noise is strongly related with pitch sequence. To reduce the pattern noise, tire's designer has to randomize the sequence of pitch. The FFT is a traditional method to evaluate the level of the randomization of the pitch sequence, but gives no information on time-varying, instantaneous frequency. In the study, we found that Time-Frequency transform is a useful method to non-stationary signal such as tire noise.

• 한국전자통신학회논문지
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• 제19권1호
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• pp.113-118
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• 2024

본 논문에서는 음향신호의 배경잡음을 소거하기 위한 시스템에서 최적의 wavelet을 제안한다. 이 시스템은 기존의 단구간 푸리에변환(STFT: Short Time Fourier Transform) 대신 이산 웨이블릿변환(DWT: Discrete Wavelet Transform)을 수행한 후 심층학습과정을 통하여 잡음소거 성능을 개선하였다. DWT는 다해상도 대역통과필터 기능을 하며 각 레벨에서 모 웨이블릿을 시간 이동시키고 크기를 스케일링한 여러 웨이블릿을 이용하여 변환 파라미터를 구한다. 여기서 음성을 분석하는데 가장 적합한 모(mother) 웨이블릿을 선정하기 위해 여러 웨이블릿에 대한 잡음소거 성능을 실험하였다. 본 연구에서 여러 웨이블릿에 대한 잡음소거시스템의 성능을 검증하기 위하여 Tensorflow와 Keras 라이브러리를 사용한 시뮬레이션 프로그램을 작성하고 가장 많이 사용되는 4개의 wavelet에 대해 모의실험을 수행하였다. 실험 결과, Haar 또는 Daubechies 웨이블릿을 사용하는 경우가 가장 우수한 잡음소거 성능을 나타냈으며 타 웨이블릿을 사용하는 경우보다 평균자승오차(MSE: Mean Square Error)가 크게 개선되는 것을 볼 수 있었다.

• 한국멀티미디어학회논문지
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• 제20권10호
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• pp.1646-1654
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• 2017

Pupil size variation can not be controlled intentionally by the user and includes various features such as the blinking frequency and the duration of a blink, so it is suitable for understanding the user's emotional state. In addition, an ocular feature based emotion classification method should be studied for virtual and augmented reality, which is expected to be applied to various fields. In this paper, we propose a novel emotion classification based on CNN with pupil size variation signals which include not only various ocular feature information but also time information. As a result, compared to previous studies using the same database, the proposed method showed improved results of 5.99% and 12.98% respectively from arousal and valence emotion classification.

• 한국생산제조학회지
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• 제8권1호
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• pp.135-141
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• 1999

Recently, advance signal analysis which is called "Time-Frequency Analysis" has been developed. Wavelet and Wigner Distribution are used to the method. Wavelet transform(WT) is applied to time-frequency analysis of waveforms obtained by an ultrasonic pulse-echo technique. The Gabor function is adopted as the analyzing wavelet. Wavelet analysis method is an attractive technique for evolution of material characterization evoluation. In this paper, the feasibility of suppression of ultrasonic background noise signal using WT has been presented. These results suggest that ultrasonic background noise ginal can be suppressed and enhanced even for SNR of 20.8 dB. This property of the WT is extremely useful for the detecting flaw echos embedded in background noise.und noise.

• 비파괴검사학회지
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• 제24권2호
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• pp.142-150
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• 2004

발전설비의 보수검사에 적용하기 위한 예비 연구로 comb transducer를 이용한 파이프 내에서의 유도초음파 모드의 거동을 실험적으로 검증하였다. 유도초음파의 모드식별은 STFT와 WT에 의한 시간-주파수해석을 통하여 최적의 모드를 선정하였다. 시간-주파수해석과 이론적 해석 방법인 분산 곡선을 비교한 결과 잘 일치함을 알 수 있었으며, pitch-catch법과 선단부로부터 반사된 신호를 모드 분석한 결과 L(0,1) 모드가 다른 모드에 비해 모드변환에 의한 영향이 적었다. 따라서 L(0,1)을 최적의 모드로 선정하고, 결함위치를 추정한 결과 유용함을 알 수 있었다.

• 한국전자파학회논문지
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• 제23권8호
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• pp.1002-1009
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• 2012

본 연구는 미시간 주립대(Michigan State University)의 바이스태틱 레이다 시스템을 통하여 수집한 측정 데이터를 이용한 표적 구분에 관한 연구 결과이다. 본 연구에서는 먼저 F-14, Mig-29, F-22 스케일 모델에 대하여 $30^{\circ}$, $60^{\circ}$, $90^{\circ}$ 바이스태틱 각도에서의 측정을 수행하였다. 측정한 데이터로부터 시간-주파수 영역 해석법인 단시간 퓨리에 변환(Short Time Fourier Transform)과 연속 웨이브릿 변환(Continous Wavelet Transform)을 이용하여 특성 벡터를 추출하고, 신경망 구분기를 통하여 표적 구분 실험을 수행하였다. 실험 결과, 바이스태틱 각도에 따라 표적 구분 성능에 많은 변화가 있으며, 특히, $60^{\circ}$ 바이스태틱 각도에서 가장 좋은 구분 성능을 가짐을 알 수 있었다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.895-902
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• 2007

Rotating machinery has two typical faults with clearance, one is partial rub and the other is looseness. Due to these faults, non-linear and non-stationary signals are occurred. Therefore, time-frequency analysis is necessary for exact fault diagnosis of rotating machinery. In this paper newly developed time-frequency analysis method, HHT(Hilbert-Huang Transform) is applied to fault diagnosis and compared with other method of FFT, SFFT and CWT. The results show that HHT can represent better resolution than any other method. Consequently, the faults of rotating machinery are diagnosed efficiently by using HHT.

• 한국음향학회지
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• 제20권8호
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• pp.81-87
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• 2001

The human auditory system is appropriate for the "constant Q"system. The STFT (Short Time Fourier Transform) is not suitable for the auditory perception model since it has constant bandwidth. In this paper, the CWT (continuous wavelet transform) is employed for the auditory filter model. In the CWT, the frequency resolution can be adjusted for auditory sensation models. The proposed CWT is applied to the modeling of the JNVF. In addition, other signal processing methods such as STFT, VER-FFT and VFR-STFT are discussed. Among these methods, the model of JNVF (Just Noticeable Variation in Frequency) by using the CWT fits in with the JNVF of auditory model although it requires quite a long time.

• 대한의용생체공학회:의공학회지
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• 제32권4호
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• pp.319-327
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• 2011

Skeletal muscle fatigue is defined as a 'any reduction in the maximal capacity to generate force or power output', and is the reduction of oxygen consumption and by-product of metabolism. For the muscle fatigue therapy, low level laser has been introduced that leads the mitochondrial respiratory and attributes the muscle fatigue recovery. This study analyzed the muscle fatigue signals from electromyography(EMG) during low-level laser therapy (LLLT). Healthy subjects performed voluntary elbow flexion-extension excercise and received placebo LLLT and active LLLT using a 830 nm laser diode. Then, EMG were measured for the evaluation of muscle fatigue. The acquired EMG data were analyzed with median frequency and short time fourier transform methods. The results showed that the LLLT had a significant symptomatic relief of muscle fatigue based on the EMG frequency analysis. Therefore, the muscle fatigue analysis with EMG signals can be applied to quantitative evaluation for the monitoring of LLLT effects.