• Journal of Communications and Networks
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• 제9권1호
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• pp.34-42
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• 2007

Orthogonal frequency division multiplexing (OFDM) combined with time division multiplexing (TDM), in this paper called OFDM/TDM, can overcome the high peak-to-average-power ratio (PAPR) problem of the conventional OFDM and improve the robustness against long time delays. In this paper, the bit error rate (BER) performance of OFDM/FDM in a frequency-selective Rayleigh fading. channel is evaluated by computer simulation. It is shown that the use of frequency-domain equalization based on minimum mean square error criterion (MMSE-FDE) can significantly improve the BER performance, compared to the conventional OFDM, by exploiting the channel frequency-selectivity while reducing the PAPR or improving the robustness against long time delays. It is also shown that the performance of OFDM/FDM designed to reduce the PAPR can bridge the conventional OFDM and single-carrier (SC) transmission by changing the design parameter.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2012년도 추계학술대회 논문집
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• pp.110-114
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• 2012

We studied on the nondestructive evaluation of the elastic wave signal of SiC ceramics and SiC/SiC composite ceramics under monotonic tensile loading. The elastic wave signal of cross and unidirectional SiC/SiC composite ceramics were obtained by pencil lead method and bending test. It was applied for the time-frequency method which used by the discrete wavelet analysis algorithm. The time-frequency analysis provides time variation of each frequency component involved in a waveform, which makes it possible to evaluate the contribution of SiC fiber frequency. The results were compared with the characteristic of frequency group from SiC slurry and fiber. Based on the results, if it is possible to shift up and design as a higher frequency group, we will can make the superior material better than those of exiting SiC/SiC composites.

• 한국해양공학회지
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• 제17권3호
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• pp.46-51
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• 2003

Acoustic emission (AE) signals, emanated during local failure of aluminum alloys, have been the subject of numerous investigations. It is well known that the characteristics of AE are strongly influenced by the previous thermal and mechanical treatment of the sample. Possible sources of AE during deformation have been suggested as the avalanche motion of dislocations, fracture of brittle particles, and debonding of these particles from the alloy matrix. The goal of the present study is to determine if AE occurring as the result of fatigue crack propagation could be evaluated by the joint time-frequency analysis method, short time Fourier transform (STFT), and Wigner-Ville distribution (WVD). The time-frequency analysis methods can be used to analyze non-stationary AE more effectively than conventional techniques. STFT is more effective than WVD in analyzing AE signals. Noise and frequency characteristics of crack openings and closures could be separated using STFT. The influence of various fatigue parameters on the frequency characteristics of AE signals was investigated.

• 한국안전학회지
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• 제26권5호
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• pp.1-6
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• 2011

Flame extinction and the chemistry of stoichiometric methane/air mixture were investigated numerically in the PSR(perfectly stirred reactor). For the study, PSR code was modified to be possible to unsteady calculation, and the sinusoidal fluctuation was subjected to the residence time. In the region of residence time far from the extinction limit, combustion mode was strongly dependent on the frequency. The low frequency excitation provided the quasi-steady behavior on the temperature and the concentrations of related species, but small variation of temperature was observed under high frequency. In the region of residence time near the extinction limit, the mixture subjected above 1 KHz was still reacting even though extinction had to be occurred under quasi-steady concept. The attenuation of extinction limit resulted from that chemical time was comparable to the flow time. The mean mole fractions of both NO and CO were almost same regardless of imposed frequency. However, the average mole fraction of $C_2H_2$ was decreased as increasing frequency, which implies that soot yield might be reduced at the higher frequency of flow excitation. The result provides the basic concept for flame stabilization, and it will be used to design a mild combustor.

• 터널과지하공간
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• 제20권2호
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• pp.112-118
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• 2010

도심지 발파와 같이 인체나 구조물에 직접적인 영향을 미칠 수 있는 발파 작업 시에는 지반진동의 영향성 평가 작업이 필수적으로 선행되어야 한다. 이로 인해 주파수가 지반진동의 특성에 관하여 미치는 영향과 피해여부를 판단하는 중요한 요소로 인식되고 있다. 주파수의 영향에 대해서 많은 연구가 이뤄지고 있지만, 이러한 연구들은 지반진동의 발생과 전파에 있어서 지연시차에 따른 주파수 특성을 연구한 것은 아니었다. 따라서 본 연구에서는 Langefors의 시차이론에 근거한 단일공 파형에 의한 중첩모델링으로 얻어진 지연시차를 통하여 지반 진동의 간섭에 있어 보강과 상쇄간섭이 반복되는 각각의 지연시차에 따른 주파수의 관계를 고찰하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권5호
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• pp.1610-1629
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• 2021

Failures frequently occurred in manufacturing machines due to complex and changeable manufacturing environments, increasing the downtime and maintenance costs. This manuscript develops a novel deep learning-based method named Multi-Domain Convolutional Neural Network (MDCNN) to deal with this challenging task with vibration signals. The proposed MDCNN consists of time-domain, frequency-domain, and statistical-domain feature channels. The Time-domain channel is to model the hidden patterns of signals in the time domain. The frequency-domain channel uses Discrete Wavelet Transformation (DWT) to obtain the rich feature representations of signals in the frequency domain. The statistic-domain channel contains six statistical variables, which is to reflect the signals' macro statistical-domain features, respectively. Firstly, in the proposed MDCNN, time-domain and frequency-domain channels are processed by CNN individually with various filters. Secondly, the CNN extracted features from time, and frequency domains are merged as time-frequency features. Lastly, time-frequency domain features are fused with six statistical variables as the comprehensive features for identifying the fault. Thereby, the proposed method could make full use of those three domain-features for fault diagnosis while keeping high distinguishability due to CNN's utilization. The authors designed massive experiments with 10-folder cross-validation technology to validate the proposed method's effectiveness on the CWRU bearing data set. The experimental results are calculated by ten-time averaged accuracy. They have confirmed that the proposed MDCNN could intelligently, accurately, and timely detect the fault under the complex manufacturing environments, whose accuracy is nearly 100%.

• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.91-94
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• 2003

In this paper, we achieve implementation of a Time-Frequency Domain Reflectometry(TFDR) system through comparatively low performance(100MS/s) PCI extensions for Instrumentation(PXI). The TFDR is the general methodology of Time Domain Reflectometry(TDR) and Frequency Domain Reflectometry(FDR). This methodology is robust in Gaussian noises, because the fixed frequency bandwidth is used. Moreover, the methodology can get more information of the fault by using the normalized time-frequency cross correlation function. The Arbitrary Waveform Generator(AWG) module generates the input signal, and the digital oscilloscope module acquires the input and reflected signals, while PXI controller module performs the control of the total PXI modules and execution of the main algorithm. The maximum range of measurement and the blind spot are calculated according ta variations of time duration and frequency bandwidth. On the basis of above calculations, the algorithm and the design of input signals used in the TFDR system are verified by real experiments. The correlation function is added to the TDR methodology for reduction of the blind spot in the TFDR system.

• 한국정보통신학회논문지
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• 제20권12호
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• pp.2401-2409
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• 2016

안드로이드 CPU 거버너는 CPU 주파수를 낮추어 CPU 공급 전압을 감소시키는 DVFS (Dynamic Voltage Frequency Scaling) 기반 전력 관리 기법을 사용한다. 그러나 CPU 주파수의 감소는 태스크의 실행 속도 지연을 유발한다. 이로 인해 태스크의 응답 시간 및 마감 시한 초과율이 증가하여 태스크가 제공하는 서비스의 품질 하락이 발생한다. 이에 본 논문에서는 다양한 안드로이드 CPU 거버너들을 전력 소비와 태스크의 응답성 및 마감 시한 측면에서 분석하였다.

• 한국소음진동공학회논문집
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• 제16권3호
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• pp.255-262
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• 2006

Frequency spectrum using the conventional Fourier analysis gives adequate information about the dynamic characteristics of the slider air bearing for the linear and stationary cases. The intermittent contacts for the extremely low flying height, however, generate nonlinear and nonstationary vibration at the instant of contact. Nonlinear dynamic model should be developed to simulate the impulse response of the air bearing during slider-disk contact. Time-frequency analysis is widely used to investigate the nonstationary signal. Several time-frequency analysis methods are employed and compared for the slider vibration signal caused by the impact against an artificially induced scratch on the disk. The representative Wigner-Ville distribution leads to the severe interference problem by cross terms even though it gives good resolution both in time and frequency. The smoothing process improves the interference problem at the expense of resolution. In order to get the results with good resolution and little interference, the reassignment method is proposed. Among others the reassigned Gabor spectrogram shows the best resolution and readability with negligible interference.