• Earthquakes and Structures
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• 제6권3호
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• pp.251-266
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• 2014

Dynamic analyses for a suite of ground of motions were conducted on concrete gravity dam sections to examine the earthquake induced stresses and effective damping. For this purpose, frequency domain methods that rigorously incorporate dam-reservoir-foundation interaction and time domain methods with approximate hydrodynamic foundation interaction effects were employed. The maximum principal tensile stresses and their distribution at the dam base, which are important parameters for concrete dam design, were obtained using the frequency domain approach. Prediction equations were proposed for these stresses and their distribution at the dam base. Comparisons of the stress results obtained using frequency and time domain methods revealed that the dam height and ratio of modulus of elasticity of foundation rock to concrete are significant parameters that may influence earthquake induced stresses. A new effective damping prediction equation was proposed in order to estimate earthquake stresses accurately with the approximate time domain approach.

• IEIE Transactions on Smart Processing and Computing
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• 제4권2호
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• pp.103-109
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• 2015

In this paper, a novel method for the classification of term and preterm birth is proposed based on time-frequency analysis of electrohysterogram (EHG) using multivariate empirical mode decomposition (MEMD). EHG is a promising study for preterm birth prediction, because it is low-cost and accurate compared to other preterm birth prediction methods, such as tocodynamometry (TOCO). Previous studies on preterm birth prediction applied prefilterings based on Fourier analysis of an EHG, followed by feature extraction and classification, even though Fourier analysis is suboptimal to biomedical signals, such as EHG, because of its nonlinearity and nonstationarity. Therefore, the proposed method applies prefiltering based on MEMD instead of Fourier-based prefilters before extracting the sample entropy feature and classifying the term and preterm birth groups. For the evaluation, the Physionet term-preterm EHG database was used where the proposed method and Fourier prefiltering-based method were adopted for comparative study. The result showed that the area under curve (AUC) of the receiver operating characteristic (ROC) was increased by 0.0351 when MEMD was used instead of the Fourier-based prefilter.

• 한국콘텐츠학회논문지
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• 제11권3호
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• pp.271-280
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• 2011

심박 변이도 (HRV) 분석은 심근허혈 (MI)를 평가하기 위한 편리한 도구이다. HRV에 대한 분석법은 시간 영역과 주파수 영역 분석으로 나눠질 수 있다. 본 논문은 단기간의 HRV 분석에 있어서 웨이블릿 변환을 주파수 영역 분석과 시간 영역 분석 비교하기 위하여 사용하였다. ST-T와 정상 에피소드는 각각 European ST-T 데이터베이스와 MIT-BIH Normal Sinus Rhythm 데이터베이스에서 각각 수집되었다. 한 에피소드는 32개 연속하는 RR 간격으로 나눠질 수 있다. 18개 HRV 특징은 시간과 주파수 영역 분석을 통하여 추출된다. 가종 퍼지소속함수 신경망 (NEWFM)은 추출된 18개의 특징을 이용하여 심근허혈을 진단하였다. 결과는 보여주는 평균 정확도로부터 시간영역과 주파수영역의 특징은 각각 75.29%와 80.93%이다.

• 대한조선학회논문집
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• 제48권4호
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• pp.299-307
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• 2011

The offshore plants such as FPSO are subjected to combination loading of environmental conditions (swell, wave, wind and current). Therefore the fatigue damage is occurred in the operation time because the units encounter the environmental phenomena and the structural configurations are complicated. This paper is a research for frequency domain fatigue analysis of wide-band random loading focused on accuracy of fatigue damage estimation regarding the proposed methods. We selected ideal bi-modal spectrum. And comparison between time-domain fatigue analysis and frequency-domain fatigue analyses are conducted through the fatigue damage ratio. Fatigue damage ratios according to Vanmarcke's bandwidth parameter are founded for wide-band. Considering safety, we recommend that Jiao-Moan and Tovo-Benasciutti methods are optimal way at the fatigue design for wide-band response. But, it is important that these methods based on frequency-domain unstably change the accuracy according to the material parameter of S-N curve. This study will be background and guidance for the new frequency-domain fatigue analysis development in the future.

• 전기학회논문지P
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• 제60권2호
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• pp.76-81
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• 2011

Power system frequency is the main index of power quality indicating an abnormal state and disturbances of systems. The nominal frequency is deviated by sudden change in generation and load or faults. Power system is used as frequency relay to detection for off-nominal frequency operation and connecting a generator to an electrical system, and V/F relay to detection for an over-excitation condition. Under these circumstances, power system should maintain the nominal frequency. And frequency and frequency deviation should accurately measure and quickly estimate by frequency measurement device. The well-known classical method, frequency estimation technique based on the DFT, could be produce the gain error in accuracy. To meet the requirements for high accuracy, recently Wavelet transforms and analysis are receiving new attention. The Wavelet analysis is possible to calculate the time-frequency analysis which is easy to obtain frequency information of signals. However, it is difficult to apply in real-time implementation because of heavy computation burdens. Nowadays, the computational methods using the Wavelet function and transformation techniques have been searched on these fields. In this paper, we apply the Recursive Discrete Wavelet Transform (RDWT) for the frequency estimation. In order to evaluate performance of the proposed technique, the user-defined arbitrary waveforms are used.

• Nuclear Engineering and Technology
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• 제56권6호
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• pp.2120-2130
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• 2024

This study significantly reduced the seismic analysis time of PCSG assembly by introducing a reduced model using homogenization and sub-structuring methods. The homogenization method was applied to the primary and secondary micro-channel sheets, and the sub-structuring method was applied to the PCSG module sets. Modal analysis and frequency response analysis were then performed to validate the accuracy of the reduced model. The analysis results were compared with the full model and it was confirmed that the reduced model provided almost the same analysis results as the full model. To verify the computational efficiency of the reduced model, the computational time was then compared with the full model, and it was confirmed that the modal analysis time was reduced by 3.42 times and the frequency response analysis time was reduced by 4.59 times.

• Communications for Statistical Applications and Methods
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• 제29권2호
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• pp.225-238
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• 2022

In this paper, we propose a clustering method for advanced metering infrastructure (AMI) data in Korea. As AMI data presents non-stationarity, we consider time-dependent frequency domain principal components analysis, which is a proper method for locally stationary time series data. We develop a new clustering method based on time-varying eigenvectors, and our method provides a meaningful result that is different from the clustering results obtained by employing conventional methods, such as K-means and K-centres functional clustering. Simulation study demonstrates the superiority of the proposed approach. We further apply the clustering results to the evaluation of the electricity price system in South Korea, and validate the reform of the progressive electricity tariff system.

• 전기학회논문지
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• 제64권3호
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• pp.498-504
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• 2015

This paper proposed an Spread Spectrum Time Domain Reflectometry (SSTDR) using time-frequency correlation analysis in order to have more accurate fault determination and location detection than classical SSTDR despite increased signal attenuation due to the long distance to cable fault location. The proposed method was validated through comparison with classical SSTDR methods in open- and short-circuit fault detection experiments of low-voltage power cables. The experimental results showed that the proposed method can detect correlation coefficients at fault locations accurately despite reflected signal attenuation so that cable faults can be detected more accurately and clearly in comparison to existing methods.

• Journal of information and communication convergence engineering
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• 제15권4호
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• pp.244-249
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• 2017

Wearable sensor-based gait analysis has been widely conducted to analyze various aspects of human ambulation abilities under the free-living condition. However, there have been few research efforts on using wearable sensors to analyze human walking on an unstable surface such as on a ship during a sea voyage. Since the motion of a ship on the unstable sea surface imposes significant differences in walking strategies, investigation is suggested to find better performing wearable sensor-based gait analysis algorithms on this unstable environment. This study aimed to compare two representative gait event algorithms including time domain and frequency domain analyses for detecting heel strike on an unstable platform. As results, although two methods did not miss any heel strike, the frequency domain analysis method perform better when comparing heel strike timing. The finding suggests that the frequency analysis is recommended to efficiently detect gait event in the unstable walking environment.

• Journal of Mechanical Science and Technology
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• 제17권2호
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• pp.197-206
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• 2003

It is intended to retrieve the time history of displacement from measured acceleration signal. In this study, the word retrieving means reconstructing the time history of original displacement signal from already measured acceleration signal not just extracting various information using relevant signal processing techniques. Unlike extracting required information from the signal, there are not many options to apply to retrieve the time history of displacement signal, once the acceleration signal is measured and recorded with given sampling rate. There are two methods, in general, to convert measured acceleration signal into displacement signal. One is directly integrating the acceleration signal in time domain. The other is dividing the Fourier transformed acceleration signal by the scale factor of - $\omega$$^2$and taking the inverse Fourier transform of it. It turned out both the methods produced a significant amount of errors depending on the sampling resolution in time and frequency domain when digitizing the acceleration signals. A simple and effective way to convert the time history of acceleration signal into the time history of displacement signal without significant errors is studied here with the analysis on the errors involved in the conversion process.