• 감성과학
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• 제16권4호
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• pp.527-534
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• 2013

본 연구에서는 코히어런스 분석을 통하여 시각집중 기간 동안 시간 변화에 대한 뇌기능과 관련된 공간-주파수간 연관관계를 해석하였다. 집중관련 시각자극 실험 데이터를 통해 ${\theta}$와 ${\alpha}$ 대역에서 서로 다른 두피 위치간 위상연관변화를 확인하였다. 좌우 전두엽, 전두엽과 두정엽 간 뇌유발전위는 P100, N200지점에서 위상동조를 보였으며, 전두엽과 후두엽 간 뇌유발전위는 시각 처리 정보가 반영되는 P300지점에서 위상동조를 보였다. 고정된 길이의 창을 이용하는 단구간 푸리에 변환에 비하여 연속 웨이블릿 변환은 모 웨이블릿의 파라미터 조정을 통한 다중해상도 분석이 가능하였다. 따라서 연속 웨이블릿 변환을 이용한 코히어런스 결과가 시간변화에 대한 뇌유발전위의 공간-주파수간 연관관계의 변화를 확인하는데 유효함을 확인하였다. 비 집중 자극수행에 대해서는 위상동조 현상이 나타나지 않았다.

• 한국항공우주학회지
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• 제32권7호
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• pp.51-59
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• 2004

저속충격에 의한 복합재의 파손 모드를 규명하기 위하여 PVDF 센서를 이용한 신호취득 방법과 측정된 PVDF 센서 신호를 시간-주파수 분석법 (time-frequency analysis)인 국소 퓨 리에 변환 및 웨이블렛 변환을 적용하여 분석할 수 있는 실험적 전차에 대하여 고찰하였다. 고분자 암전센서를 이용하여 저속충격시 발생할 수 있는 여러 충격손상 형태 모재균열, 층간분리, 섬유파단에 의한 응력파 측정 가능성을 고찰하기 위하여 일련의 저속충격 시험을 수행하였다. 충격 시험 후, 저속 충격을 받은 적층판에 대하여 C-scan 과 단면 검사를 통하여 센서 신호, 손상 모드 및 크기에 대한 상관관계를 고찰하였다. 센서신호의 취득과 신호분석을 통하여 저속충격의 발생/진행과정을 알 수 있는 많은 중요한 정보가 PVDF 센서신호에도 내재되어 있음을 알 수 있으며 PVDF 센서 신호를 주의 깊게 분석함으로써 저속 충격에 의한 복합재료의 손상 모드 규명이 가능하며 저속충격 위협에 대한 복합재 구조물의 건전성 모니터링에 활용할 수 있는 가능성을 제시하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 추계학술대회 논문집 전력기술부문
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• pp.283-285
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• 2005

This paper presents a new two-terminal numerical algorithm for fault location estimation and for faults recognition using the synchronized phasor in time-domain. The proposed algorithm is also based on the synchronized voltage and current phasor measured from the PMUs(Phasor Measurement Units) installed at both ends of the transmission lines. Also the arc voltage wave shape is modeled numerically on the basis of a great number of arc voltage records obtained by transient recorder. From the calculated arc voltage amplitude it can make a decision whether the fault is permanent or transient. In this paper the algorithm is given and estimated using DFT(Discrete Fourier Transform) and the LES(Least Error Squares Method). The algorithm uses a very short data window and enables fast fault detection and classification for real-time transmission line protection. To test the validity of the proposed algorithm, the Electro-Magnetic Transient Program(EMTP/ATP) and MATLAB is used.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2002년도 춘계학술대회 논문집
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• pp.44-50
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• 2002

The fast Fourier transform (FFT) is a good method to estimate spectral density, but the frequency resolution is limited to the sampling window, and thus the precise characteristics of the spectral density for short signals are not clear. To solve the limitation, a multiple band-pass filter was introduced to estimate the precise time course of the spectral density for flash visual evoked potentials (VEPs). Signals were recorded during -200 and 600 ms using balanced noncephalic electrodes, and sampled at 1 K Hz in 12 bits. With 1 Hz and 10 ms resolutions, spectral density was estimated between 10 and 100 Hz. Background powers at the alpha-and beta-bands were high over the posterior scalp, and powers around 200ms were evoked at the same bands over the same region, corresponding to P110 and N165 of VEPs. normalized's spectral density showed evoked powers around 200 ms and suppressed powers following the evoked powers over the posterior scalp. The evoked powers above the 20Hz band were not statistically significant. However, the gamma band was significantly evoked intra-individually; details in the gamma bands were varied among the subjects. Details of spectral density were complicated even for a simple task such as watching flashes; both synchronization and desynchronization occurred with different distributions and different time courses.

• 한국전자파학회논문지
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• 제22권10호
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• pp.981-989
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• 2011

본 논문에서는 광대역 레이다 측정 신호를 이용하여 5기종의 스케일 모델에 대해 표적 구분 실험을 수행하였다. 대역폭의 크기에 따른 표적 구분 성능을 비교하기 위해 2 GHz(2~4 GHz), 4 GHz(2~6 GHz), 그리고 6 GHz(2~8 GHz)의 대역폭을 이용하였고, 시간-주파수 영역 해석법인 STFT와 CWT를 이용하여 각 표적에 대한 특성벡터를 추출하였다. 여기서 추출된 특성 벡터들은 multi-layerd perceptron(MLP) 신경망 구분기의 입력으로 사용되어 표적 구분 성능을 비교한 결과, 사용하는 주파수 대역폭이 넓을수록 표적 구분 성능이 향상되는 것을 확인할 수 있었다.

• 한국전자파학회논문지
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• 제21권12호
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• pp.1460-1466
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• 2010

본 논문은 바이스태틱 RCS와 모노스태틱 RCS를 이용하여 각각 표적 구분 실험을 수행하고 그 성능을 비교 분석하였다. 모노스태틱 및 바이스태틱 RCS로부터 특성을 추출하기 위하여 시간-주파수 영역 해석법인 STFT와 CWT를 이용하였으며, 다중 퍼셉트론 신경망을 구분기로 이용하였다. 실험 결과, 모노스태틱과 바이스태틱 RCS 모두 CWT가 STFT보다 더 나은 구분 성능을 보여주었다. 또한, STFT에서는 바이스태틱 RCS를 이용했을 때, CWT에서는 모노스태틱 RCS를 이용하였을 때 대체적으로 더 좋은 성능을 나타내었다. 결과적으로 본 논문을 통하여 바이스태틱 RCS도 모노스태틱 RCS처럼 표적 구분에 똑같이 적용할 수 있다는 것을 알 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.348-369
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• 2024

With the advancement of Industry 4.0 and Industrial Internet of Things (IIoT), manufacturing increasingly seeks automation and intelligence. Temperature and vibration monitoring are essential for machinery health. Traditional abnormal state detection methodologies often overlook the intricate frequency characteristics inherent in vibration time series and are susceptible to erroneously reconstructing temperature abnormalities due to the highly similar waveforms. To address these limitations, we introduce synergistic, end-to-end, unsupervised Frequency-Time Domain Memory-Enhanced Autoencoders (FTD-MAE) capable of identifying abnormalities in both temperature and vibration datasets. This model is adept at accommodating time series with variable frequency complexities and mitigates the risk of overgeneralization. Initially, the frequency domain encoder processes the spectrogram generated through Short-Time Fourier Transform (STFT), while the time domain encoder interprets the raw time series. This results in two disparate sets of latent representations. Subsequently, these are subjected to a memory mechanism and a limiting function, which numerically constrain each memory term. These processed terms are then amalgamated to create two unified, novel representations that the decoder leverages to produce reconstructed samples. Furthermore, the model employs Spectral Entropy to dynamically assess the frequency complexity of the time series, which, in turn, calibrates the weightage attributed to the loss functions of the individual branches, thereby generating definitive abnormal scores. Through extensive experiments, FTD-MAE achieved an average ACC and F1 of 0.9826 and 0.9808 on the CMHS and CWRU datasets, respectively. Compared to the best representative model, the ACC increased by 0.2114 and the F1 by 0.1876.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2378-2387
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• 2017

Violinists learn to make better sounds by hearing and evaluating their own playing though numerous practice. This study proposes a new method of auditory feedback, which mimics this violinists' step and verifies its efficiency using experiments. Making the desired sound quality of a violin is difficult without auditory feedback even though an expert violinist plays. An algorithm for controlling a robot arm of violin playing robot is determined based on correlations with bowing speed, bowing force, and sound point that determine the sound quality of a violin. The bowing speed is estimated by the control command of the robot arm, where the bowing force and the sound point are recognized by using a two-axis load cell and a photo interrupter, respectively. To improve the sound quality of a violin playing robot, the sounds information is obtained by auditory feedback system applied Short Time Fourier Transform (STFT) to the sounds from a violin. This study suggests Gaussian-Harmonic-Quality (GHQ) uses sounds' clarity, accuracy, and harmonic structure in order to decide sound quality, objectively. Through the experiments, the auditory feedback system improved the performance quality by the robot accordingly, changing the bowing speed, bowing force, and sound point and determining the quality of robot sounds by GHQ sound quality evaluation system.

• 비파괴검사학회지
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• 제33권3호
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• pp.264-269
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• 2013

Since MFC(macro-fiber composite) transducer has been developed, many researchers have tried to apply this transducer on SHM(structural health monitoring), because it is so flexible and durable that it can be easily embedded to various kinds of structures. The objective of this paper is to figure out the benefits and feasibility of applying MFC transducers to guided wave technique. For this, we have experimentally tested the performance of MFC patches as transmitter and sensors for excitation and reception of guided waves on the thin aluminum alloy plate. In order to enhance the signal accuracy, we applied the FIR filter for noise reduction as well as used STFT(short-time Fourier transform) algorithm to image the guided wave characteristics clearly. From the results, the guided wave generated based on MFC showed good agreement with its theoretical dispersion curves. Moreover, the ultrasonic Lamb wave techniques based on MFC patches in pitch-catch manner was tested for detection of surface notch defects of which depths are 10%, 20%, 30% and 40% of the aluminum plate thickness. Results showed that the notch was detectable well when the notch depth was 10% of the thickness or greater.

• 전기학회논문지
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• 제56권12호
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• pp.2184-2188
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• 2007

We developed a novel method of partial discharge(PD) location based on the fact that the waveform of PD signal propagate along the GIB (Gas Insulated Bus) is composed of several modes of electromagnetic wave with different group velocities and cut-off frequencies. From the PD waveform, measured at a broadband PD sensor attached on the GIB, we could derive arrival time and frequency components of different modes using the short term Fourier transform or etc. After the group velocities of different modes are calculated, the location of the PD source could be estimated. To show the effectiveness of this new locating method in a real on site application, we used this method to locate the position of a PD source at a 76 m long 345 kV GIB substation. The estimated location of the PD source using the method proposed above was in good agreement with the actual location found from the inspection result of internal component in the GIB with 2.4% of the estimation error.