• Journal of the Korean Society for Nondestructive Testing
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• v.18 no.3
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• pp.191-204
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• 1998

One of the key issues in acoustic emission (AE) during hydroproof test of filament-wound composite rocket motor cases is the determination of the optimal component of elastic wave to be monitored. To solve this problem, broadband ultrasonic wave was generated into a symmetrically filament-wound composite motor case, and was received at 105 different locations after the propagation through the composite case with different distances and directions. By analysis of the received signals, characteristics of elastic wave propagation such as frequency components, the maximum propagating distance, and velocity surface were investigated. This analysis was performed for two different conditions of the motor case; air-filled and hydraulically pressurized. Based on these information, the effect of hydraulic pressure on the wave propagation characteristics was investigated and furthermore, the optimal component of elastic wave for AE during hydroproof test of the motor case was successfully determined.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.05a
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• pp.134-139
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• 2002

Fracture behaviors of pipes with local wall thinning are very important for the integrity of nuclear power plant. However, effects of local wall thinning on strength and fracture behaviors of piping system were not well studied. Acoustic emission(AE) has been widely used in various fields because of its extreme sensitivity, dynamic detection ability and location of growing defects. In this study, we investigated failure modes of locally wall thinned pipes and AE signals by bending test. From test results, we could be divided four types of failure modes of ovalization, crack initiation after ovalization, local buckling and crack initiation after local buckling. And fracture behaviors such as elastic region, yielding range, plastic deformation range and crack progress could be evaluated by AE counts, accumulative counts and time-frequency analysis during bending test. It is expected to be basic data that can protect a risk according to local wall thinning of pipes, as a real time test of AE.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.3
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• pp.284-290
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• 2014

Aluminum alloy is a core material for structural parts of aircraft and automobiles to reduce the weight and maintain high specific strength. This study evaluates the machinability and investigates the optimal cutting conditions considering the surface integrity and productivity for Al7050-T7451 milling. The machining variables considered are the feed per tooth, spindle speed, axial depth of the cut, and radial depth of the cut. The machinability evaluation of Al7050-T7451 is conducted by analyzing the cutting force signals, acceleration signals, AE signals, and machined surface conditions. The optimal cutting conditions are determined by analyzing the experimental results using response surface methodology for stable machining considering the productivity and surface integrity.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1487-1496
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• 2013

In this paper, a novel algorithm for PD localization in power transformers based on wavelet de-noising technique and energy criterion is proposed. Partial discharge is one of the main failures in power transformers. The localization of which could be very useful for maintenance systems. Acoustic signals due to a PD event are transient, irregular and non-repetitive. So wavelet transform is an efficient tool for this signal processing problem that gives a time-frequency demonstration. First, different wavelet based de-noising methods are analyzed. Then, a reasonable structure for threshold value determining and applying manner on signals is presented. Evaluated errors are good evidences for choices. Next, applying the elimination low energy frequency bands is discussed and developed as a de-noising method. Time differences between signals are used for PD localization. Different ways in time arrival detection are introduced and a novel approach in energy criterion method is presented. At the end, the quality of algorithm is verified through the different assays in lab.

• Proceedings of the PSK Conference
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• 2002.10a
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• pp.229-229
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• 2002

Although hepatocellular dysfunction occurs during sepsis. the mechanism responsible for this remains unclear. Since Kupffer cells provide signals that regulate hepatic response in endotoxin and inflammation. the aim of this study was to investigate the role of Kupffer cells in the alterations in the hepatic microsomal drug metabolizing function during sepsis. Rats were subjected to polymicrobial sepsis by cecal ligation and puncture (CLP)followed by fluid resuscitation. (omitted)

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.231-232
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• 2019

최근 압축감도 부호화라는 새로운 기술의 개발로 인하여 기존보다 더 빠른 검사시간에 자기공명영상 검사가 가능하게 되었다. 감도 부호화를 이용한 터보 스핀 에코 확산강조 자기공명영상과 비교하였을 때, 압축감도 부호화를 사용한 확산강조영상에서 영상평가와 자기공명 신호 분석을 통해 적절한 영상품질을 유지하면서, 검사시간을 줄 일수 있어 확산강조영상에서에 유용하게 사용되리라 사료된다.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.641-650
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• 2010

Color image sensors (CIS) output color images through image sensors and image signal processing. Image sensors that convert light to electrical signal are divided into CMOS image sensor and CCD image sensor according to transferring method of signal charge. In general, a CIS has RGB output signals from tri-stimulus XYZ of the scene through image signal processing. This paper presents an adaptive colorimetric analysis method to obtain chromaticity and luminance using CIS under various environments. An image sensor for the use of colorimeter is characterized based on the CIE standard colorimetric observer. We use the method of least squares to derive a colorimetric characterization matrix between camera RGB output signals and CIE XYZ tristimulus values. We first survey the camera characterization in the standard environment then derive a SGL(shutter-gain-level) function which is relationship between luminance and auto exposure (AE) characteristic of CIS, and read the status of an AWB(auto white balance) function. Then we can apply CIS to measure luminance and chromaticity from camera outputs and AE resister values without any preprocessing. Camera RGB outputs, register values, and camera photoelectric characteristic are used to analyze the colorimetric results for real scenes such as chromaticity and luminance. Experimental results show that the proposed method is valid in the measuring performance. The proposed method can apply to various fields like surveillant systems of the display or security systems.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.184-192
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• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.

• Journal of the Korean Institute of Gas
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• v.9 no.3 s.28
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• pp.1-8
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• 2005

We studied on the nondestructive evaluation of the elastic wave signals of locally wall thinned straight pipe. Wavelet transform was applied for the time-frequency analysis of waveforms obtained by fracture wave detector due to the dropping steel ball. The time-frequency analysis provides time variation of each frequency component involved in a waveform, which makes it possible to evaluate the shape of local wall thinning at each frequency. In this study, comparison by wavelet transform of the AE signals and monotonic bending tests without internal pressure are conducted on 1.91 inch diameter full-scale carbon steel pipe specimens. As the results of tests, fracture behaviors could be shown by the characteristic of mechanical strength of locally wall thinned pipes and the waveforms could be evaluated for the integrity insurance of the piping system according to the length and depth range of the deffeted shape pipes in the real field.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.5
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• pp.343-352
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• 2006

In the present paper, the nondestructive test method was suggest to establish the bonding status of a motor case assembly composed of a steel motor case, adiabatic rubber layer and an ablative composite tube with strain data, AE(acoustic emission) signals and UT(ultrasonic test) data. And, finite element analysis was conducted to verify quantitatively the bonding status of motor case assembly under inner pressure loading. The bonding status could be judged whether the bonding status is perfect or contact condition by the data correlation study with AE signals and strain data measured from air pressure test. And, to classify the bonding status of motor case and rubber layer among bonding layers, UT method was also applied. From this study, the bonding status could be classified and detected into fourth types for all bonding layers as follows: (1) initial un-bonding, (2) perfect do-bonding during an air pressure test, (3) partially de-bonding during an air pressure test, and (4) perfect bonding.