• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.81-88
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• 2018

Spectrum sensing, the key technology of the cognitive radio networks, is used by a secondary user to determine the frequency state of a primary user. The energy detection in the spectrum sensing determines the presence or absence of a primary user according to the intensity of the allocated channel signal. Since this technique simply uses the strength of the signal for spectrum sensing, it is difficult to detect the signal of a primary user in the low SNR band. In this paper, we propose a way to combine spectrum sensing and support vector machine using wavelet packet decomposition to overcome performance degradation in low SNR band. In our proposed scheme, the sensing signals were extracted by wavelet packet decomposition and then used as training data and test data for support vector machine. The simulation results of the proposed scheme are compared with the energy detection using the AUC of the ROC curve and the accuracy according to the SNR band. With simulation results, we demonstrate that the proposed scheme show better determining performance than one of energy detection in the low SNR band.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.308-315
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• 2009

Because the attenuation of AE signal in composite materials is relatively higher than that of metallic materials, it is required to develop a damage assessment technique less affected by the attenuation property of composite materials in order to use AE sensing as a damage detection method. In the signal processing procedure, it is profitable to use the leading wave that arrives first because the leading wave is less influenced by the boundary conditions. Using wavelet transform, we investigated the frequency characteristics of impact induced AE signals focused on the leading wave in advance and chose the key factors to discriminate the damaged condition quantitatively. In this research, we established a damage assessment technique using the sharing percentage of the wavelet detail components of AE signal, and conducted a low-velocity impact test on composite laminates to confirm the feasibility of the proposed signal processing method.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.672-678
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• 2009

Acoustic Emission (AE) technique is a non-destructive testing method and widely used for the early detection of faults in rotating machines in these days, because the sensitivity of AE transducers is higher than normal accelerometers. So it can detect low energy vibration signals. The faults in the rotating machines are generally occurred at bearings and gearboxes which are the principal parts of the machines. It was studied to detect the bearing faults by envelop analysis in several decade years. And the researches showed that AE had a possibility of the application in condition monitoring system(CMS) using the envelope analysis for the rolling bearing. And peak ratio (PR) was developed for expression of the bearing condition in condition monitoring system using AE. Noise level is needed to reduce to take exact PR value because the PR is calculated from total root mean square (RMS) and the harmonics peak levels of the defect frequencies of the bearing. Therefore, in this paper, the discrete wavelet transform (DWT) was added in the envelope analysis to reduce the noise level in the AE signals. And then, the PR was calculated and compared with general envelope analysis result and the result of envelope analysis added the DWT. In the experiment result about inner fault of bearing, defect frequency was difficult to find about only envelop analysis. But it's easy to find defect frequency after wavelet transform. Therefore, Envelop analysis added wavelet transform was useful method for early detection of default in signal process.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.1
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• pp.31-34
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• 2006

A simple robust fundamental frequency estimator on the time-frequency domain is proposed. Combined with the appropriately designed low-pass filter, the instantaneous frequency estimator based on the Teager-Kaiser energy function can detect the fundamental frequency of speech signal. The Teager-Kaiser function can be obtained through real computation and show the change of frequency as time goes. And when a speech block with N samples is processed with a lowpass fille. with length of L, it requires $O(N{\cdot}(L+5))operations,$ compared to $O(N{\cdot}2log_2N+L))operations$ in the recently introduced wavelet and conventional instantaneous frequency method. The computer simulation confirms the usefulness of the proposed fundamental frequency estimation method.

• Journal of Korea Multimedia Society
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• v.7 no.9
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• pp.1246-1254
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• 2004

This paper presents a image coding method that is well adaptive to close-range video transmission because of its low titrate and simple coding procedure. At first, it reduces temporal redundancies by performing image DPCM between previous frame and current frame, and makes wavelet transformed image of this difference image. Then, the coefficients are quantized selectively by using the coefficient values of base level and mid-frequency level because inter-level redundancies are widely exists in multi-resolution images. Finally quantized coefficients are made iron the function that implies the target bitrate, the average coefficient energy, and the value of the level. The proposed method shows the effective Performance in the experiments using the continuous motion images and transition images.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.5
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• pp.71-79
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• 2015

Recently, new Low Voltage DC (LVDC) power distribution systems have been constantly researched as uses of DC in end-user equipment are increased. As in conventional AC distribution system, High Impedance Fault (HIF) which may cause a failure of protective relay can occur in LVDC distribution system as well. It, however, is hard to be detected since change in magnitude of current due to the fault is too small to detect the fault by the protective relay using overcurrent element. In order to solve the problem, this paper presents an algorithm for detecting HIF using accumulated energy in LVDC distribution system. Wavelet Singular Value Decomposition (WSVD) is used to extract abnormal high frequency components from fault current and accumulated energy of high frequency components is considered as the element to detect the fault. LVDC distribution system including AC/DC and DC/DC converter is modeled to verify the proposed algorithm using ElectroMagnetic Transient Program (EMTP) software. Simulation results considering various conditions show that the proposed algorithm can be utilized to effectively detect HIF.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.174-184
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• 2013

For the successful R&D and deployment of LED-based green energy lighting systems, the real-time power quality measurement of both various non-linear power signals including pulse waveform, spike waveform, etc and the undesired-signals including harmonics, sag, swell, etc is required. In this paper, we propose a low-cost power quality measurement (PQM) method for low- (60Hz-several KHz) to high-frequency (several tens KHz) power signals, which are generated by green-energy lighting systems, and implement a PQM testbed using TI TMS320F28335 MCU. The proposed algorithm is programmed using C in the CCS (Code Composer Studio) 3.3 environment and is verified using test signals generated by an arbitrary signal generator, NF-WF1974. In the implemented testbed, we can measure various non-linear current signals that LED SMPS generates, analyze harmonics by fast Fourier transform, and test sag, swell, and interruption using wavelet transform.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.110-112
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• 2002

In this paper, a new technique for Thai isolated speech phoneme segmentation is proposed. Based on Thai speech feature, the isolated speech is first divided into low and high frequency components by using the technique of wavelet decomposition. Then the energy contour of each decomposed signal is computed and employed to locate phoneme boundary. To verity the proposed scheme, some experiments have been performed using 1,000 syllables data recorded from 10 speakers. The accuracy rates are 96.0, 89.9, 92.7 and 98.9% for initial consonant, vowel, final consonant and silence, respectively.

• Corrosion Science and Technology
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• v.16 no.4
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• pp.194-200
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• 2017

Stress-corrosion cracking (SCC) of alloy 600 and alloy 800 in 0.5 mol/L thiosulfate solution during constant strain was investigated using electrochemical noise (EN) combined with 3-D microscope techniques. The in-situ morphology observation and EN results indicate that the SCC process could be divided into three stages: (1) passive film stabilization and growth, (2) crack initiation, (3) and crack growth. Power Spectral Density (PSD) and the probability distribution obtained from EN were used as the "fingerprint" to distinguish the different processes. During passive film stabilization and growth, the current noise signals resembled "white noise": when the crack initiated, many transient peaks could be seen in the current noise and the wavelet energy at low frequency as well as the noise resistance decreased. After crack propagation, the noise amplitudes increased, particularly the white noises at low and high frequencies ($W_L$ and $W_H$) in the PSDs. Finally, the detection of metal structure corrosion in a simulated sea splash zone and pipeline corrosion in the atmosphere are established.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.7
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• pp.51-59
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• 2004

An experimental procedure to identify failure modes of impact damage using sensor signals and to analyze their general features is examined. A series of low-velocity impact tests from low energy to damage-induced high energy were performed on the instrumented drop weight impact tester to monitor the stress wave signals due to failure modes such as matrix cracking, delamination, and fiber breakage. The wavelet transform(WT) and Short Time Fourier Transform(STFT) are used to decompose the piezoelectric sensor signals in this study. The extent of the damage in each case was examined by means of a conventional ultrasonic C-scan. The PVDF sensor signals are shown to carry important information regarding the nature of the impact process that can be extracted from the careful signal processing and analysis.