• Earthquakes and Structures
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• 제11권6호
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• pp.1143-1164
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• 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.

• Communications for Statistical Applications and Methods
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• 제22권2호
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• pp.159-172
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• 2015

This paper considers the problem of reconstructing an underlying signal from noisy data. This paper presents a reconstruction method based on synchrosqueezed wavelet transform recently developed for multiscale representation. Synchrosqueezed wavelet transform based on continuous wavelet transform is efficient to estimate the instantaneous frequency of each component that consist of a signal and to reconstruct components. However, an objective selection method for the optimal number of intrinsic mode type functions is required. The proposed method is obtained by coupling the synchrosqueezed wavelet transform with cross-validation scheme. Simulation studies and musical instrument sounds are used to compare the empirical performance of the proposed method with existing methods.

• 대한원격탐사학회지
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• 제38권5_1호
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• pp.587-596
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• 2022

기후 변화로 인하여 해수면은 상승 추세에 있으며, 이로 인해 해안가 주변 저지대는 물에 잠길 위험에 처해있다. 따라서 본 연구에서는 위성 고도계 자료(Topex/Poseidon, Jason-1/2/3) 및 Southern Oscillation Index(SOI) /Pacific Decadal Oscillation (PDO) 자료를 이용하여 해수면 높이 변화와 기후 지수간의 관계를 알아보고자 하였다. 시간 기반의 함수를 주파수 기반 함수 형태로 변환시킨다면 각 자료가 가지고 있는 고유 주기를 분석할 수 있다. 푸리에 변환과 웨이블릿 변환은 대표적인 주기 분석 방법이다. 푸리에 변환은 주기에 대한 정보만 획득 가능하지만, 웨이블릿 변환은 주기 및 시간 정보 둘 다 획득할 수 있다. 웨이블릿 변환은 각 자료에 대한 주기를 찾을 수 있으며, 교차 웨이블릿 변환과 웨이블릿 긴밀도는 두 자료에 대한 공통 주기나 상관 관계 및 위상을 찾을 수 있다. 교차 웨이블릿 변환 결과 해수면 높이 및 두 기후 지수(SOI, PDO)의 1년 주기에서 강한 출력이 확인되었으며, 해수면 높이와 PDO는 역위상 관계를 보였다. 웨이블릿 긴밀도 분석에서는 교차 웨이블릿 변환에서 나타나지 않았던 1년 미만의 단주기 및 장주기에서의 상관관계가 높은 구간을 찾을 수 있었다. 웨이블릿 분석은 각 자료의 주기를 찾을 수 있을 뿐만 아니라 두 시계열 자료가 가지고 있는 주기 및 위상관계를 찾을 수 있었다. 따라서 본 연구 결과는 웨이블릿 분석을 통해 기후 자료가 가지는 고유의 주기를 분석하는 데 사용될 수 있을 것이며 시계열 자료 분석에서 찾기 어려운 해양의 다양한 현상을 모니터링하는데 활용할 수 있을 것으로 판단된다.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 추계학술발표회논문집(1)
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• pp.225-230
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• 1997

Discrete Wavelet Transforms (DWTs) are recent mathematics, and begin to be used in various fields. The wavelet transform can be used to compress the signal and image due to its inherent properties. We applied the wavelet transform compression and reconstruction to the neutron cross section data. Numerical tests illustrate that tile signal compression using wavelet is very effective to reduce the data saving spaces.

• Smart Structures and Systems
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• 제1권2호
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• pp.185-215
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• 2005

Advanced signal processing techniques have been long introduced and widely used in structural health monitoring (SHM) and nondestructive evaluation (NDE). In our research, we applied several signal processing approaches for our embedded ultrasonic structural radar (EUSR) system to obtain improved damage detection results. The EUSR algorithm was developed to detect defects within a large area of a thin-plate specimen using a piezoelectric wafer active sensor (PWAS) array. In the EUSR, the discrete wavelet transform (DWT) was first applied for signal de-noising. Secondly, after constructing the EUSR data, the short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used for the time-frequency analysis. Then the results were compared thereafter. We eventually chose continuous wavelet transform to filter out from the original signal the component with the excitation signal's frequency. Third, cross correlation method and Hilbert transform were applied to A-scan signals to extract the time of flight (TOF) of the wave packets from the crack. Finally, the Hilbert transform was again applied to the EUSR data to extract the envelopes for final inspection result visualization. The EUSR system was implemented in LabVIEW. Several laboratory experiments have been conducted and have verified that, with the advanced signal processing approaches, the EUSR has enhanced damage detection ability.

• Smart Structures and Systems
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• 제16권1호
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• pp.213-222
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• 2015

Early detection and precise location of leakage is of great importance for life-cycle maintenance and management of municipal pipeline system. In the past few years, acoustic emission (AE) techniques have demonstrated to be an excellent tool for on-line leakage detection. Regarding the multi-mode and frequency dispersion characteristics of AE signals propagating along a pipeline, the direct cross-correlation technique that assumes the constant AE propagation velocity does not perform well in practice for acoustic leak location. This paper presents an improved cross-correlation method based on wavelet transform, with due consideration of the frequency dispersion characteristics of AE wave and the contribution of different mode. Laboratory experiments conducted to simulate pipeline gas leakage and investigate the frequency spectrum signatures of AE leak signals. By comparing with the other methods for leak location identification, the feasibility and superiority of the proposed method are verified.

• 디지털산업정보학회논문지
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• 제14권2호
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• pp.49-59
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• 2018

Encryption of digital images has been requested various fields. In the meantime, many algorithms based on a text - based encryption algorithm have been proposed. In this paper, we propose a method of encryption in wavelet transform domain to utilize the characteristics of digital image. In particular, wavelet transform is used to reduce the association between the encrypted image and the original image. Wavelet packet transformations can be decomposed into more subband images than wavelet transform, and various position permutation, numerical transformation, and visual transformation are performed on the coefficients of this subband image. As a result, this paper proposes a method that satisfies the characteristics of high encryption strength than the conventional wavelet transform and reversibility. This method also satisfies the lossless symmetric key encryption and decryption algorithm. The performance of the proposed method is confirmed by visual and quantitative. Experimental results show that the visually encrypted image is seen as a completely different signal from the original image. We also confirmed that the proposed method shows lower values of cross correlation than conventional wavelet transform. And PSNR has a sufficiently high value in terms of decoding performance of the proposed method. In this paper, we also proposed that the degree of correlation of the encrypted image can be controlled by adjusting the number of wavelet transform steps according to the characteristics of the image.

• 전자공학회논문지S
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• 제34S권2호
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• pp.94-103
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• 1997

The WCHF-FSJTC (wavelet circular harmonic function frequency selective joint transform correlator) using th wavelet transformed CHF as the reference image in FSJTC is proposed for rotation invariant pattern recognition. Since the wavelet transform has the property of feature extraction, the proposed system can have the better DC (discrimination cpability) and the higher SNR(signal to noise ratio) compared with the conventional CHF-CJTC(circular harmonic function conventional joint transform correlator). And since the structure of the proposed system is FSJTC which can eliminate auto-correlation and cross-correlation between input images, it can eliminate false alarm caused by the overlapping among correlation peaks. The used wavelet functio is the morlet function, which is proper for the reference image used in this paper. the optimal dialation parameter and oscillation frequency of the wavelet function are also achieved with varying the parameters of the wavelet function. The computer simulation shows that the proposed system has the best performance when the dilation parameter is 0.8 and the oscillation frequency is 0.48.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.457-458
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• 2013

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.695-706
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• 2014

Partial discharge (PD) measurements have emerged as a dominant investigative tool for condition monitoring of insulation in high voltage equipment. But the major problem behind them the PD signal is severely polluted by several noises like White noise, Random noise, Discrete Spectral Interferences (DSI) and the challenge lies with removing these noise from the onsite PD data effectively which leads to preserving the signal for feature extraction. Accordingly the paper is mainly classified into two parts. In first part the PD signal is artificially simulated and mixed with white noise. In second part the PD is measured then it is subjected to the proposed denoising techniques namely Translation Invariant Wavelet Transform (TIWT). The proposed TIWT method remains the edge of the original signal efficiently. Additionally TIWT based denoising is used to suppress Pseudo Gibbs phenomenon. In this paper an attempt has been made to review the methodology of denoising the PD signals and shows that the proposed denoising method results are better when compared to other wavelet-based approaches like Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), by evaluating five different parameters like, Signal to noise ratio, Cross-correlation coefficient, Pulse amplitude distortion, Mean square error, Reduction in noise level.