• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.969-971
• /
• 1999

Wavelet analysis is applying to many fields such as the time-frequency localization of a time series and a time varying data. In this paper, a statistical testing based Wavelet power spectrum analysis for the stationary Nino3 Sea Surface Temperature(SST) data was executed. Specially, the 95% confidence level for SST was effective in searching the periods of El-Nino using various wavelet basis functions.

• Structural Engineering and Mechanics
• /
• v.22 no.2
• /
• pp.185-195
• /
• 2006

Nowadays it is very necessary to generate artificial accelerograms because of lack of adequate earthquake records and vast usage of time-history dynamic analysis to calculate responses of structures. According to the lack of natural records, the best choice is to use proper artificial earthquake records for the specified design zone. These records should be generated in a way that would contain seismic properties of a vast area and therefore could be applied as design records. The main objective of this paper is to present a new method based on wavelet theory to generate more artificial earthquake records, which are compatible with target spectrum. Wavelets are able to decompose time series to several levels that each level covers a specific range of frequencies. If an accelerogram is transformed by Fourier transform to frequency domain, then wavelets are considered as a transform in time-scale domain which frequency has been changed to scale in the recent domain. Since wavelet theory separates each signal, it is able to generate so many artificial records having the same target spectrum.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.8 no.3 s.22
• /
• pp.73-82
• /
• 2005

This paper describes shock waveform synthesis methods for a shock response spectnlm over a short time interval with which intereference between parts within a test item is increased to perform a sufficient shock test for damage or malfunction which may be caused by the interference between parts, and a digital filter for obtaining a shock response history required for the shock waveform synthesis and a digital inverse filter for restoration by inversely using the digital filter. The time at which the maximax value occurs in the response history is detected in order to establish a delay time which is one of the parameters in the wavelet, on the condition that the natural frequency of SDOF system with a Q (quality factor) of 10 equals to the wavelet frequency of the zero delay wavelet input. A shock response spectrum over a short time interval and an abrupt change in the acceleration for an instant are illustrated as features of the synthesized waveform.

• Earthquakes and Structures
• /
• v.12 no.4
• /
• pp.389-395
• /
• 2017

In this paper a simple approach is presented for spectral matching of ground motions utilizing the wavelet transform and a recently developed metaheuristic optimization technique. For this purpose, wavelet transform is used to decompose the original ground motions to several levels, where each level covers a special range of frequency, and then each level is multiplied by a variable. Subsequently, the vibrating particles system (VPS) algorithm is employed to calculate the variables such that the error between the response and target spectra is minimized. The application of the proposed method is illustrated through modifying 12 sets of ground motions. The results achieved by this method demonstrate its capability in solving the problem. The outcomes of the VPS algorithm are compared to those of the standard colliding bodies optimization (CBO) to illustrate the importance of the enhancement of the algorithm.

• Journal of the Korean Society of Propulsion Engineers
• /
• v.2 no.2
• /
• pp.88-98
• /
• 1998

A waveform for shock response spectrum test on a shaker is synthesized using wavelets such that a specified shock response spectrum of a test profile is achieved. The parameters of a wavelet are center frequency, amplitude, number of half cycles, delay and polarity. The amplitude of each wavelet component is iteratively adjusted so a specified shock response spectrum is matched. The waveform so synthesized is regarded as a reference acceleration waveform for a shaker shock response spectrum test. The author proposes the use of a long duration and low peak waveform. The usefulness of this approach is illustrated with some examples.

• Earthquakes and Structures
• /
• v.11 no.6
• /
• pp.1143-1164
• /
• 2016

Time Delay of Arrival (TDOA) estimation methods based on correlation function analysis play an important role in the micro-seismic event monitoring. It makes full use of the similarity in the recorded signals that are from the same source. However, those methods are subjected to the noise effect, particularly when the global similarity of the signals is low. This paper proposes a new approach for micro-seismic monitoring based on cross wavelet transform. The cross wavelet transform is utilized to analyse the measured signals under micro-seismic events, and the cross wavelet power spectrum is used to measure the similarity of two signals in a multi-scale dimension and subsequently identify TDOA. The offset time instant associated with the maximum cross wavelet transform spectrum power is identified as TDOA, and then the location of micro-seismic event can be identified. Individual and statistical identification tests are performed with measurement data from an in-field mine. Experimental studies demonstrate that the proposed approach significantly improves the robustness and accuracy of micro-seismic source locating in mines compared to several existing methods, such as the cross-correlation, multi-correlation, STA/LTA and Kurtosis methods.

• Journal of the Institute of Convergence Signal Processing
• /
• v.8 no.3
• /
• pp.178-184
• /
• 2007

The EEG signal in general can be categorized as the Alpha wave, the Beta wave, the Theta wave, and the Delta wave. The alpha wave, showed in stable state, is the dominant wave for a human EEG and the beta wave displays the excited state. The subject of this paper was to recognize the stable state of EEG quantitatively using wavelet transform and power spectrum analysis. We decomposed EEG signal into the alpha wave and the beta wave in the process of wavelet transform, and calculated each power spectrum of EEG signal, using Fast Fourier Transform. And then we calculated the stable state quantitatively by stable state ratio, defined as the power spectrum of the alpha wave over that of the beta wave. The study showed that it took more than 10 minutes to reach the stable state from the normal activity in 69 % of the subjects, 5 -10 minutes in 9%, and less than 5 minutes in 16 %.

• Journal of Korean Clinical Health Science
• /
• v.4 no.4
• /
• pp.756-761
• /
• 2016

Purpose. Noise occurs at measuring Electoretinogram(ERG) signals as the other bio-signal measurement. It is compared the denoising performance according to the mother function of wavelet transforms. Methods. The ERG signal that generated power supply noise and white noise was used as a sampling signal. The noise of ERG signal was filtered by using haar, db7, bior mother function. The filtering performance of each mother functions was compared using Fourier transform spectrum and SNR(signal to noise ratio). Results. In the haar functioin, the result of the Fourier transform spectrum was that the power supply noise is removed and the white noise performance is not good. The SNR was 27.0404. In the db7 function, the results of Fourier transform spectrum was that the power supply noise is removed and the white noise performance is good. The SNR was 35.1729. In the db7 function, the results of Fourier transform spectrum was that the power supply noise is removed and the white noise performance is the bset. The SNR was 35.4445. Conclusions. The db7, bior function was good results in power supply noise and white noise filtered. The bior function is suitable for filtering noise of the ERG signal.

• Journal of the Korea Society for Simulation
• /
• v.19 no.2
• /
• pp.127-135
• /
• 2010

The validation of a simulation model is a key to demonstrate that the simulation model is reliable. However, among various validation methods have been introduced, it is very poor to research the specific techniques for the time series data. Therefore, this paper suggests the methodology to verify the simulation using the time series data by Wavelet Transform, Power Spectrum and Coherence. This method performs 2 steps as followed. Firstly, we get spectrum using the Wavelet transform available for non-periodic signal separation. Secondly, we compare 2 patterns of output data from simulation model and actual system by Coherence Analysis. As a result of comparing it with other validation techniques, the suggested way can judge simulation model accuracy more clearly. By this way, we can make it possible to perform the simulation validation test under various situations using detailed sectional validation method, which has been impossible using a single statistics for the whole model.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
• /
• 2000.10a
• /
• pp.118-122
• /
• 2000

In this study, Ringing is investigated by continuous wavelet transform. Ringing is considered to be one of the typical transient phenomena in the field of ocean engineering. The wavelet analysis is adopted to analyze ringing from the point that wavelet analysis is capable of frequency analysis as well as time domain analysis. The use mother wavelet is the Morlet wavelet. The relation between the frequency of the time series and that of wavelet can be clearly defined with Mor1et wavelet. Experimental data obtained by other researchers was used. The wave height time series and acceleration times series of the surface piercing cylinder were analyzed. The results show that the proposed scheme can detect typical frequency region by the time domain analysis which could hardly be detected if one relied on the frequency analysis.