• Korean Journal of Optics and Photonics
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• v.15 no.1
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• pp.46-50
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• 2004

Images were acquired by the modulation of terahertz electromagnetic signals and compared by modulation frequencies. For the real-time acquisition of images a fast scanning method has been adopted utilizing a galvanometer. The acquired time domain waveforms were transformed into frequency domain data by fast Fourier transformations (FFT). We chose some frequency components to compare the resolution of images. The beam profiles at the focal position were measured by a knife-edge technique. Beam diameter was shown to decrease as the frequency increased. By scanning one- and two-dimensional samples a significant image enhancement was observed with the frequency increment. A nondesouctive imaging system using ㎔ electromagnetic pulses was also demonstrated.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.115-126
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• 2023

Due to the fluctuating random and periodical nature of renewable energy generation power quality disturbances occurred more frequently in power generation transformation transmission and distribution. Various power quality disturbances may lead to equipment damage or even power outages. Therefore it is essential to detect and classify different power quality disturbances in real time automatically. The traditional PQD identification method consists of three steps: feature extraction feature selection and classification. However, the handcrafted features are imprecise in the feature selection stage, resulting in low classification accuracy. This paper proposes a deep neural architecture based on Convolution Neural Network and Long Short Term Memory combining the time and frequency domain features to recognize 16 types of Power Quality signals. The frequency-domain data were obtained from the Fast Fourier Transform which could efficiently extract the frequency-domain features. The performance in synthetic data and real 6kV power system data indicate that our proposed method generalizes well compared with other deep learning methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.495-513
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• 2020

The correlation identification of the subsurface is a novel electrical prospecting method which could suppress stochastic noise. This method is increasingly being utilized by geophysicists. It achieves the frequency response of the underground media through division of the cross spectrum of the input & output signal and the auto spectrum of the input signal. This is subject to the spectral leakage when the cross spectrum and the auto spectrum are computed from cross correlation and autocorrelation function by Discrete Fourier Transformation (DFT, "To obtain an accurate frequency response of the earth system, we propose an improved correlation identification method which uses all phase Fast Fourier Transform (APFFT) to acquire the cross spectrum and the auto spectrum. Simulation and engineering application results show that compared to existing correlation identification algorithm the new approach demonstrates more precise frequency response, especially the phase response of the system under identification.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.34-42
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• 1997

This paper deals with the recognition of closed planar shape using a three dimensional spectral feature vector which is derived from the FFT(Fast Fourier Transform) spectrum of contour sequence and fuzzy ARTMAP neural network classifier. Contour sequences obtained from 2-D 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 Fourier transform of contour sequence and spectrum analyzer are used as a means of feature selection and data reduction. The three dimensional spectral feature vectors are extracted by spectrum analyzer from the FFT spectrum. These spectral feature vectors are invariant to shape translation, rotation and scale transformation. The fuzzy ARTMAP neural network which is combined with two fuzzy ART modules is trained and tested with these feature vectors. The experiments including 4 aircrafts and 4 industrial parts recognition process are presented to illustrate the high performance of this proposed method in the recognition problems of noisy shapes.

• Journal of Korean Association for Spatial Structures
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• v.20 no.2
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• pp.77-85
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• 2020

This paper examined the dynamic instability of a shallow arch according to the response characteristics when nearing critical loads. The frequency changing feathers of the time-domain increasing the loads are analyzed using Fast Fourier Transformation (FFT), while the response signal around the critical loads are analyzed using Hilbert-Huang Transformation (HHT). This study reveals that the models with an arch shape of h = 3 or higher exhibit buckling, which is very sensitive to the asymmetric initial conditions. Also, the critical buckling load increases as the shape increases, with its feather varying depending on the asymmetric initial conditions. Decomposition results show the decrease in predominant frequency before the threshold as the load increases, and the predominant period doubles at the critical level. In the vicinity of the critical level, sections rapidly manifest the displacement increase, with the changes in Instantaneous Frequency (IF) and Instant Energy (IE) becoming apparent.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.11a
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• pp.255-259
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• 2001

본 연구에서는 긍/부정 판단 과제 시 연령간 뇌파 반응의 차이를 밝히고자 한다. 실험 대상의 연령은 10명(20대 5명, 60대 5명)이었으며, 모두 오른손잡이였다. 실험과제는 의미과제와 일화과제로 구분되며 각각 12문항으로 구성된다. 의미기억과제 덧셈문제를, 일화기억 과제는 도형을 이용하였으며, 마우스 버튼을 눌러 긍/부정 판단 반응을 하도록 하였다. 뇌파는 PE1, PF2, F3, F4, O1, O2에서 단극유도법으로 측정되었으며, EOG를 측정하여 뇌파분석 시에 눈 깜박임으로 인하 noise를 제거하도록 하였다. 뇌파 분석은 원자료를 FFT(Fast Fourier Transformation)를 수행하여 각 대역의 상대적인 power를 구하는 방법으로 이루어졌다. 분석 결과, 반응 시간은 긍/부정판단간의 차이는 없었으나, 두 과제 모두에서 연령별로 유의미한 차이가 있었다. 긍/부정판단간의 따른 뇌파 반응은 명확한 차이가 나타나지 않았다. 연령에 따른 뇌파반응은 theta파, slow beta, fast beta에서 유의한 차이가 나타났다.

• Journal of Power Electronics
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• v.19 no.1
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• pp.307-315
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• 2019

Condition monitoring has been recognized as an effective and low-cost method to enhance the reliability and improve the maintainability of power electronic converters. In power electronic converters, high-frequency oscillation occurs during the switching transients of power transistors, which is known as ringing. The ringing frequency mainly depends on the values of the parasitic capacitance and stray inductance in the oscillation loop. Although circuit stray inductance is an important factor that leads to the ringing, it does not change with transistor aging. A shift in either the inside inductance or junction capacitance is an important failure precursor for power transistors. Therefore, ringing frequency can be used to monitor the health of power transistors. However, the switching actions of power transistors usually result in a dynamic behavior that can generate oscillation signals mixed with background noise, which makes it hard to directly extract the ringing frequency. A frequency extraction method based on empirical mode decomposition (EMD) and Fast Fourier transformation (FFT) is proposed in this paper. The proposed method is simple and has a high precision. Simulation results are given to verify the ringing analysis and experimental results are given to verify the effectiveness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.41-46
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• 2009

This research measures EEG signals which are generating on head skin and extracts brain concentration level related with brain activity. We develop concentration wireless transmission system for controlling hardware by using this signal. Two channels are used for measuring EEG signal on front head and Biopac system with MP100 and EEG100C was used for measuring EEG signal, amplifying and filtering the signal. LabView 8.5 was also used for FFT transformation, frequency and spectrum analysis of the measured EEG signals. As a result, SMR wave, Mid-Bata wave, $\Theta$ wave classified. We extracted the concentration index by adapting concentration extraction algorithm. This concentration uldex was transferred into logo automobile device by wireless module and applied for BCI application.

• Korean Journal of Applied Biomechanics
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• v.15 no.4
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• pp.117-129
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• 2005

The purpose of this study was to characterize the impact shock wave and its attenuation, and the kinematic response of the lower extremity's joints to the impact shock during downhill running in which the lower extremity's extensor acts dominantly. For this study, fifteen subjects(mean age:$27.08{\pm}4.39$; mass:$76.30{\pm}6.60$; height:$177.25{\pm}4.11$) were required to run on the 0% grade treadmill and downhill grades of 7%, and 15% in random at speed of their preference. When the participant run, acceleration at the tibia and the sacrum and kinematic data of the lower extremity were collected for 20s so as to provide at least 5 strides for analysis at each grade. Peak impact accelerations were used to calculate shock attenuation between the tibia and sacrum in time domain at each grade. Fast Fourier transformation(FFT) and power spectral density(PSD) techniques were used to analyze impact shock factors and its attenuation in the frequency domain. Joint coordinate system technique was used to compute angular displacement of the ankle and knee joint in three dimension. The conclusions were drawn as fellows: 1. Peak impact accelerations of the tibia and sacrum in downhill run were greater than that of 0% grade run, but no significant between conditions. Peak shock of PSD resembled also in pattern of peak impact acceleration. The wave of impact shock attenuation between the tibia and sacrum decreased with increasing grade, but didn't find a significant difference between grade conditions. 2. Adduction/abduction, flexion/extention, and internal/external rotation of the ankle and knee joints at support phase between grade conditions didn't make much difference. 3. At grade of 7% and 15%, there were relationship between the knee of the flexion/extension movement and peak impact acceleration during heel strike and found also it in the ankle of plantar/dorsiflexion at grade of 15%.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.37-41
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• 2007

Fast Fourier Transformation(FFT) is one of the most useful way to analyze response signal for the purpose of grasping the dynamic characteristics of system. Excitation is a factor or process making noise or vibration. It's typical and simple experimental method widely used for catching hold of dynamic peculiar characters and modal behaviors of system by frequency analysis. There are harmonic excitation, impact excitation, random excitation, sweep excitation, chirp excitation and so on as the ideal method in an experiment using exciter. In this thesis, excitation testing module for NI-PXI equipment is developed. The analyzing module is developed with LabVIEW tool. A user can generate each waveform for shaking a structure and see quickly and easily modal shape of system with this module. This developed module will be expected to build up more convenient and serviceable measurement system.