• Journal of the Korean Society for Nondestructive Testing
• /
• v.30 no.3
• /
• pp.261-270
• /
• 2010

This paper presents an analytical investigation for a baseline-free imaging of a defect in plate-like structures using the time-reversal of Lamb waves. We first consider the flexural wave (A0 mode) propagation in a plate containing a defect, and reception and time reversal process of the output signal at the receiver. The received output signal is then composed of two parts: a directly propagated wave and a scattered wave from the defect. The time reversal of these waves recovers the original input signal, and produces two additional side bands that contain the time-of-flight information on the defect location. One of the side band signals is then extracted as a pure defect signal. A defect localization image is then constructed from a beamforming technique based on the time-frequency analysis of the side band signal for each transducer pair in a network of sensors. The simulation results show that the proposed scheme enables the accurate, baseline-free detection of a defect, so that experimental studies are needed to verify the proposed method and to be applied to real structure.

• Proceedings of the KSME Conference
• /
• 2000.04a
• /
• pp.67-72
• /
• 2000

Demand for now nondestructive evaluation are growing to detect fatigue crack growth behavior to predict long term performance of materials and structure in aggressive environments especially when they are In non-visible area. Acoustic emission technique is well suited to these problems and has drawn a keen interests because of its dynamic detection ability, extreme sensitivity and location of growing defects. In this study, we analysed acoustic emission signals obtained in fatigue and tensile test of high strength fire resistance steel for frame structure with time-frequency analysis methods. The main frequency range is different in the noise and the fatigue crack propagation. It could be classified that it were also generated by composite fracture mechanics of cleavage, dimple, inclusion separation etc.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.9
• /
• pp.1583-1589
• /
• 2016

This paper proposes an improved spread spectrum time domain reflectometry (ISSTDR) using time-frequency correlation and reference signal elimination method in order to have more accurate fault determination and location detection than conventional (SSTDR) despite increased signal attenuation due to the long distance to cable fault location. The proposed method has a two-step process: the first step is to detect a peak location of the reference signal using time-frequency correlation analysis, and the second step is to detect a peak location of the correlation coefficient of the reflected signal by removing the reference signal. The proposed method was validated through comparison with existing 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 the Korea Society for Simulation
• /
• v.25 no.3
• /
• pp.15-28
• /
• 2016

It is necessary to analyze underwater acoustics channel(UAC) modeling and simulation for underwater weapon system development and acquisition. In order to analyze UAC, there are underwater acoustics propagation numerical analysis models(Ray theory, Parabolic equation, Normal-mode, Wavenumber integration). However, If these models are used for multiple frequency signal analysis, they are inaccurate to calculate result of analysis effectiveness and restricted for signal processing and analysis. In this paper, to overcome this problem, we propose simple/multiple frequency signal analysis model of the Pseudospectral Time-Domain Method synthetic environment UAC applied to underwater environment noise model as like as realistic underwater environment. In order to confirm the validation of the model, we performed the 9 scenarios simulation(4 scenarios of single frequency signal, 4 scenarios of multiple frequency signal, 1 scenario of single/multiple frequency signal like submarine radiated noise) for validation and confirmed the validation of this model through the simulation model.

• Journal of the Korean Institute of Telematics and Electronics T
• /
• v.35T no.3
• /
• pp.37-45
• /
• 1998

In this paper, the different frequency component and time informations from an EMI signal are extracted simultaneously using a wavelet transform and the results of transform in the time and frequency domain are analyzed. Frequencies are extracted from the EMI signal by performing the multiresolution analysis using the Daubechies-4 filter coefficients and the time information through the results of wavelet transform. We have tried the correlation analysis to evaluate the results of wavelet transform. We have chosen the optimal wavelet function for an object signal by comparing the transformed results of various wavelet functions and verified the simulation examples of waveform and harmonic analysis using a wavelet transform. We have proved the denoising effect to the EMI signal using the soft thresholding technique.

• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.2
• /
• pp.63-69
• /
• 2019

In this study, bispectrum analysis method introduced to reduce variability of SEF(spectral edge frequency) and MF(median frequency), which are the anesthetic depth indexes extracted by EEG spectral analysis. Bispectrum analysis is an analytical method that can confirm the nonlinearity of EEG. Signal measurement and analysis in the surgical environment should take into consideration various external artifact factors. Bispectrum analysis can confirm the presence of externally introduced artifacts, thereby effectively eliminating artifacts that affect the EEG signal. By applying bispectrum parameters, real-time variability of the anesthetic depth parameters SEF, MF could be reduced. Elimination of variability makes it possible to use SEF, MF as a real-time index during surgery.

• Journal of KSNVE
• /
• v.8 no.4
• /
• pp.749-756
• /
• 1998

기어에서 충격성 진동 및 소음은 치차의 이상과 연관이 있다. 따라서 충격 진동 및 소리는 기어의 이상 진단에 사용되어 질 수 있다. 또한 이들 충격파를 조기에 정확하게 탐지하여 기어의 이상을 진단하면 완전 파손을 방지할 수 있다. 그러나 주변 소음 및 노이즈 신호 때문에 객관적이 충격파의 탐지가 어렵기 때문에, 본 논문은 이러한 숨겨진 충격 신호를 능동 신호 처리 기법을 이용하여 조기에 찾아내고 이것을 시간-주파수 영역에서 해석하였다.

• Proceedings of the IEEK Conference
• /
• 2001.06d
• /
• pp.285-288
• /
• 2001

In the speech analysis, to estimate formant center frequencies exactly is very important. If we know formant frequencies, we can expect which pronunciation is uttered. Generally, the magnitude of first formant frequency in voiced speech is 10dB more than other formant frequency. So, the shape of voice signal in time domain is affected by mainly first formant. Therefore we can get first formant frequency roughly by using ZCR(Zero Cross Rate). In this paper, we proposed the improvement method to get first formant frequency by using ZCR. We did autocorrelation before getting ZCR. This procedure makes voice signal smooth so, first formant in voice signal is emphasized. As a result of this method, we got more exact ZCR and first formant frequency. Conventional method of formant estimate is done in frequency domain but proposed method is done in time domain. So, this is very simple.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.4
• /
• pp.1375-1384
• /
• 2014

Flashover of power transmission line insulators is a major threat to the reliable operation of power system. This paper deals with the flashover prediction of polymeric insulators used in power transmission line applications using the novel condition monitoring technique developed by PD signal time-frequency map and neural network technique. Laboratory experiments on polymeric insulators were carried out as per IEC 60507 under AC voltage, at different humidity and contamination levels using NaCl as a contaminant. Partial discharge signals were acquired using advanced ultra wide band detection system. Salient features from the Time-Frequency map and PRPD pattern at different pollution levels were extracted. The flashover prediction of polymeric insulators was automated using artificial neural network (ANN) with back propagation algorithm (BPA). From the results, it can be speculated that PD signal feature extraction along with back propagation classification is a well suited technique to predict flashover of polymeric insulators.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.9 no.2 s.25
• /
• pp.118-126
• /
• 2006

As weapon systems are becoming advanced and intelligent, they are designed to have such events like ejecting sub-munitions. So it is continually requested to measure the event time and position exactly. We can measure the event time and position by analyzing the complex signal of the instrumentation radar in the time domain and can also obtain the spin rate of the target by analyzing the complex signal in the frequency domain.