• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.10-17
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• 2008

The purpose of this thesis is to reduce of error for source location through acoustic emission(AE) signal, generated elastic wave from crack growth to leak for facility diagnosis. Especially, in order to overcome noise from original signal, this paper proposed enhancement of source location by using noise reduction based on wavelet transform. To evaluate actual performance in experiments, Pencil Lead Break is used crack signal source on the aluminum plate and drain valve of air compressor is used as substitute pressure vessel to generate leak signal. In signal processing, wavelet shrinkage and soft threshold are used to discriminate signal source and then source location techniques have been effectively used with group velocity using material property and time difference between sensor using cross correlation. Source location for crack and leak test have some difference, but the result show that improved 30% with a average length within 10.46mm in crack test and improved 2% compare with average filter in leak test when we applied wavelet transform.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.923-926
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• 2000

In this paper we address the problem of detecting and estimating an unknown narrow band signal in a noise interference environment A new practical band estimation method, yielding good performance even in case of finite-length data, is presented. More specifically, wavelet packet transform is utilized to detect the more accurate time-variant band, then we estimate the power from wavelet filter-coefficients of the respective band. Also, third-order cumulants, and projection cross-correlation (PCC) criterion are utilized to achieve an effective SNR improvement for the time-variant band estimation. In case of time variant band estimation, the PCC method yields better performance than the correlation method.

• Journal of the Korean Geophysical Society
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• v.4 no.2
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• pp.113-120
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• 2001

The discrete wavelet transform(DWT) has potential as a tool for supplying discriminatory attributes with which to distinguish seismic events. The wavelet transform has the great advantage over the Fourier transform in being able to localize changes. In this study, a discrete wavelet transform is applied to seismic traces for identifying seismic events and picking of arrival times for first breaks and S-wave arrivals. The precise determination of arrival times can greatly improve the quality of a number of geophysical studies, such as velocity analysis, refraction seismic survey, seismic tomography, down-hole and cross-hole survey, and sonic logging, etc. provide precise determination of seismic velocities. Tests for picking of P- and S- wave arrival times with the wavelet transform method is conducted with synthetic seismic traces which have or do not have noises. The results show that this picking algorithm can be successfully applied to noisy traces. The first arrival can be precisely determined with the field data, too.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.2
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• pp.118-128
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• 1999

There are many ultrasonic measurement methods that are used in nondestructive testing applications. Some typical applications include material property determination, microstructural characterization. and flaw detection. Ultrasonic parameters such as velocity and attenuation are most commonly required in these applications. The accuracy and repeatability of testing results are dependent on both the hardware used to generate and receive the ultrasonic waves and on the analysis software for calculating these parameters. In this study, five analysis algorithms were implemented on a computer for measuring wave speed in a pulse echo. immersion testing configuration. In velocity measurements comparisons were made between the overlap. cross-correlation. Fourier transform. Hilbert transform, wavelet transform algorithms. Velocity measurement was applied to an isotropic steel sample using the five analysis algorithms. Frequency-dependent phase/group velocity and attenuation were also measured using the Fourier transform and wavelet transform algorithms on a composite laminate containing voids.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.11
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• pp.1555-1565
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• 2010

This paper presents a new method for indentifying the location of impact source in a buried duct. In a gas pipeline, the problem of leakage occurs due to the mechanical load exerted by construction equipment. Such leakage can cause catastrophic disasters in gas supply industries. Generally, the cross-correlation method has been used for indentifying the location of impact source in a pipeline. Since this method involves the use of the dispersive acoustic wave, it derives an amount of error in process of estimating the time delay between acoustic sensors. The object of this paper is to estimate the time delay in the arrival of the direct wave by using the wavelet transform instead of the dispersive wave. The wavelet transform based method gives more accurate estimates of the impact location than the cross-correlation method does. This method is successfully used to identify the location of impact force in an actual buried gas duct.

• Journal of the Korean Geotechnical Society
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• v.24 no.4
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• pp.115-123
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• 2008

The dispersive phase velocity of a wave propagating through multilayered systems such as a soil site is an important parameter and carries valuable information in non-destructive site characterization tests. The dispersive phase velocity of a wave can be determined using the phase spectrum, which is easily evaluated through the cross power spectrum. However, the phase spectrum determined using the cross power spectrum is easily distorted by background noise which always exists in the field. This causes distortion of measured signal and difficulties in the determination of the dispersive phase velocities. In this paper, a new method to evaluate the phase spectrum using the harmonic wavelet transform is proposed and the phase spectrum by the proposed method is applied to the determination of dispersion curve. The proposed method can successfully remove background noise effects. To evaluate the validity of the proposed method, numerical simulations of multi-layered systems were performed. Phase spectrums and dispersion curves determined by the proposed method were found to be in good agreement with the actual phase spectrums and dispersion curves biased by heavy background noise. The comparison manifests the proposed method to be a very useful tool to overcome noise effects.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1899-1909
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• 2015

Glaucoma is one of the most common causes of blindness which is caused by increase of fluid pressure in the eye which damages the optic nerve and eventually causing vision loss. An automated technique to diagnose glaucoma disease can reduce the physicians’ effort in screening of Glaucoma in a person through the fundal retinal images. In this paper, optimal hyper analytic wavelet transform for Glaucoma detection technique from fundal retinal images is proposed. The optimal coefficients for transformation process are found out using the hybrid GSO-Cuckoo search algorithm. This technique consists of pre-processing module, optimal transformation module, feature extraction module and classification module. The implementation is carried out with MATLAB and the evaluation metrics employed are accuracy, sensitivity and specificity. Comparative analysis is carried out by comparing the hybrid GSO with the conventional GSO. The results reported in our paper show that the proposed technique has performed well and has achieved good evaluation metric values. Two 10- fold cross validated test runs are performed, yielding an average fitness of 91.13% and 96.2% accuracy with CGD-BPN (Conjugate Gradient Descent- Back Propagation Network) and Support Vector Machines (SVM) respectively. The techniques also gives high sensitivity and specificity values. The attained high evaluation metric values show the efficiency of detecting Glaucoma by the proposed technique.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.319-324
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• 2005

An integrated approach for prostate cancer detection using proteomic data is presented. Due to the high-dimensional feature of proteomic data, the discrete wavelet transform (DWT) is used in the first-stage for data reduction as well as noise removal. After the process of DWT, the dimensionality is reduced from 43,556 to 1,599. Thus, each sample of proteomic data can be represented by 1599 wavelet coefficients. In the second stage, a voting method is used to select a common set of wavelet coefficients for all samples together. This produces a 987-dimension subspace of wavelet coefficients. In the third stage, the Autoassociator algorithm reduces the dimensionality from 987 to 400. Finally, the artificial neural network (ANN) is applied on the 400-dimension space for prostate cancer detection. The integrated approach is examined on 9 categories of 2-class experiments, and also 3- and 4-class experiments. All of the experiments were run 10 times of ten-fold cross-validation (i. e. 10 partitions with 100 runs). For 9 categories of 2-class experiments, the average testing accuracies are between 81% and 96%, and the average testing accuracies of 3- and 4-way classifications are 85% and 84%, respectively. The integrated approach achieves exciting results for the early detection and diagnosis of prostate cancer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1C
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• pp.56-63
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• 2003

In this paper, a wavelet-based stereo matching algorithm to obtain an accurate disparity map in wavelet transformed domain by using a shift ability property, a modified wavelet transform, the similarities for their sub-bands, and a hierarchical structure is proposed. New approaches for stereo matching by lots of feature information are to utilize translation-variant results of the sub-bands in the wavelet transformed domain because they cannot literally expect translation invariance in a system based on convolution and sub-sampling. After the similarity matching for each sub-band, we can easily find optimal matched-points because the sub-bands appearance of the shifted signals is definitely different from that of the original signal with no shift.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.5
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• pp.513-518
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• 2008

The research of global-scale mass redistribution and it changed by Earth gravity filed variation observations, including Earth's oblateness $J_2$(also called low degree spherical harmonic coefficient $C_{20}$), is in continuous progress. Recently, the comparative analysis of geodetic observation SLR can be made by the development of GRACE and other time-variable gravity measurements. In this study, $C_{20}$ time series changes in the value of comparative analysis was got by GRACE monthly Gravity filed model (CSR RL04) for the period April 2002 to May 2008. And comparative analysis the harmonic coefficients of $C_{20}$ was obtained from SLR observations. Signal analysis for two time-series data was made by wavelet transform, CWT(continuous wavelet transform), XWT(cross wavelet transform) and WTC(wavelet coherence) methods. The results indicate that GRACE and SLR values for $C_{20}$ had both decreasing trend, as well as SLR data represent the annual frequencies, and GRACE was semiannual variations. In addition, the results of GRACE and SLR had a strong correlation with the XWT and WTC in an annual cycle.