• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.4
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• pp.62-68
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• 2001

In this paper, As the wavelet transform has the properties of multi-resolution analysis and time-frequency domain localization, application of wavelet transform is used at partial discharge(PD) signal detected by electrical detection method to extract PD signal's various frequency component and its time domain. therefore we can analyzed PD signal's time-frequency domain simultaneously. On the other hand, using wavelet transform denoising process, included noise signal in detected PD signal is well eliminated. we can propose the true shine of PD signal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.2
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• pp.141-154
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• 2013

The technology of precise time-synchronization between signal receive devices for separation distance operation can be a key point for the technology with TDoA-based system. We propose a new method for the higher accuracy of system's time-synchronization in this paper, which uses OCXO and DPLL with high accuracy to achieve phase synchronization at 1 pps (pulse per second) of signal. And the method receive time value from a GPS satellite. Essentially, the performance of GPS with high accuracy refers to long-term frequency stability for its reliability. As per the characteristic, as the GPS timing signals are synchronized continuously, the accuracy of time-synchronization gets improved proportionally. Therefore, if the time synchronization is accomplished, the accuracy of the synchronization can be up to 0.001 ppb (part per billion). Through the improved accuracy of the time-synchronization, the measurement error of TDOA-based location detection technology is evaluated. Consequently, we verify that TDoA-based location measurement error can be greatly improved via using the improved method for time-synchronization error.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.739-742
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• 2007

In the step processing multimedia information signals transmitted by a variety of mediums, noises are generated by the internal or exterior causes of systems and these noises degrade the perception about information signals. Therefore, in order to remove noises and restore signals a great number of researches have been progressed and recently, many noise removal methods using time-frequency localization of wavelet have been applied in wide applications. Moreover, when two wavelet bases are designed to accomplish the Hilbert transform pair, wavelet can be efficiently applied to detect characteristics of signals. Therefore, in this paper, in order to restore the corrupted signal by noises, a noise removal algorithm using the Hilbert transform pair of wavelet was proposed.

• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.1247-1256
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• 2008

Based on two real and invertible $d{\times}d$ matrices Band C such that the norm $||C^T\;B||$ is sufficiently small, we provide a construction of tight Gabor frames $\{E_{Bm}T_{Cn}g\}_{m,n{\in}{\mathbb{Z}^d}$ with explicitly given and compactly supported generators. The generators can be chosen with arbitrary polynomial decay in the frequency domain.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.147-148
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• 2008

In this paper two kinds of techniques were compared for localization of PD(partial discharge) in power transformer and more useful method was suggested. Both of them, the time of arrival and the energy content method, were tested in 154kV single phase experimental transformer using UHF signal measurement. The former was using the difference of arrival time of recorded signals from four UHF sensors, the latter was based on the energy content in frequency spectra of signals detected at all sensors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5527-5545
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• 2019

Through-wall ultra-wide band (UWB) radar has been considered as one of the preferred and non-contact technologies for the targets detection owing to the better time resolution and stronger penetration. The high time resolution is a result of a larger of bandwidth of the employed UWB pulses from the radar system, which is a useful tool to separate multiple targets in complex environment. The article emphasised on human subject localization and detection. Human subject usually can be detected via extracting the weak respiratory signals of human subjects remotely. Meanwhile, the range between the detection object and radar is also acquired from the 2D range-frequency matrix. However, it is a challenging task to extract human respiratory signals owing to the low signal to clutter ratio. To improve the feasibility of human respiratory signals detection, a new method is developed via analysing the standard deviation based kurtosis of the collected pulses, which are modulated by human respiratory movements in slow time. The range between radar and the detection target is estimated using joint time-frequency analysis (JTFA) of the analysed characteristics, which provides a novel preliminary signature for life detection. The breathing rates are obtained using the proposed accumulation method in time and frequency domain, respectively. The proposed method is validated and proved numerically and experimentally.

• Journal of Mechanical Science and Technology
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• v.20 no.12
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• pp.2147-2158
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• 2006

The continuous wavelet transform (CWT) has a frequency-adaptive time-frequency tiling property, which makes it popular for the analysis of dispersive elastic wave signals. However, because the time-frequency tiling of CWT is not signal-dependent, it still has some limitations in the analysis of elastic waves with spectral components that are dispersed rapidly in time. The objective of this paper is to introduce an advanced time-frequency analysis method, called the dispersion-based continuous wavelet transform (D-CWT) whose time-frequency tiling is adaptively varied according to the dispersion relation of the waves to be analyzed. In the D-CWT method, time-frequency tiling can have frequency-adaptive characteristics like CWT and adaptively rotate in the time-frequency plane depending on the local wave dispersion. Therefore, D-CWT provides higher time-frequency localization than the conventional CWT. In this work, D-CWT method is applied to the analysis of dispersive elastic waves measured in waveguide experiments and an efficient procedure to extract information on the dispersion relation hidden in a wave signal is presented. In addition, the ridge property of the present transform is investigated theoretically to show its effectiveness in analyzing highly time-varying signals. Numerical simulations and experimental results are presented to show the effectiveness of the present method.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.178-183
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• 2024

This study introduces an enhanced sound source localization technique, bolstered by a data-driven deep learning approach, to improve the precision and accuracy of direction of arrival estimation. Focused on refining Time Difference Of Arrival (TDOA) based sound source localization, the research hinges on accurately estimating TDOA from cross-correlation functions. Accurately estimating the TDOA still remains a limitation in this research field because the measured value from actual microphones are mixed with a lot of noise. Additionally, the digitization process of acoustic signals introduces quantization errors, associated with the sampling frequency of the measurement system, that limit the precision of TDOA estimation. A deep learning-based approach is designed to overcome these limitations in TDOA accuracy and precision. To validate the method, we conduct comprehensive evaluations using both two and three-microphone array configurations. Moreover, the feasibility and real-world applicability of the suggested method are further substantiated through experiments conducted in an anechoic chamber.

• Journal of Sensor Science and Technology
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• v.30 no.2
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• pp.105-108
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• 2021

Detection and localization of partial discharge are considered critical techniques for estimating the lifetimes of power cables. High-frequency current transformers (HFCTs) are commonly used for the detection of partial discharge in high-voltage alternating current (HVAC) power cables; however, their applicability is compromised by the limitations of the installation locations. HFCTs are typically installed in cable terminals or insulation joint boxes because HVACs induce strong time-varying magnetic fields around the cables, saturating the ferromagnetic materials in the HFCTs. Therefore, partial discharges near the installation locations can be detected. In this study, the feasibility of partial discharge detection using a HFCT was investigated for high-voltage direct current (HVDC) cables. We demonstrated that the HFCT could be installed at any location in the HVDC power cable to monitor partial discharge along the entire cable length. Furthermore, we showed that the HFCT could detect the location of partial discharge with high accuracy.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1771-1772
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• 2006

In this paper, we considered multiple faults detection on a coaxial cable through Time-Frequency Domain Reflectometry (TFDR). It is well known that TFDR has high resolution accuracy for detecting and estimating the fault detection on a coaxial cable. This approach was based on time-frequency signal analysis and utilized a chirp signal multiplied by a Gaussian time envelope. The Gaussian envelope provided time localization, while the chirp allowed one to excite the system interest. We carried out experiments with 10C-FBT coaxial cable having either one or two faults. The result shows TFDR can be extended to detect multiple faults with high accuracy on a coaxial cable.