• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.367-370
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• 2001

This paper proposes a new deterioration diagnostic technique for power facilities by analyzing the pulse-height analysis of leakage current. Until now, various deterioration diagnostic techniques to prevent power system failures by deterioration of power facilities are suggested, and most of which measures leakage current amplitude only as a estimation parameter. In this experiment, it is known that the pulse heights of the leakage current are increased according to deterioration progress as well as there comes remarkable changes in pulse height distribution thereto. Therefore, the use of pulse height distribution in deterioration diagnostic technique makes more accurate diagnosis than the conventional method by using only leakage current value. From the application test, it is confirmed that the proposed technique has sufficient performance to diagnose deterioration of power facilities.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.129-136
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• 2019

In this study, the magnetic flux leakage technique was applied to diagnose steel plate damage, imaging technique was applied through those signals. Steel plate specimens with different thicknesses were prepared for the imaging the magnetic flux leakage signal, and 6 different depths of damage were artificially processed at the same locations on each specimen. The sensor head consist hall sensor and magnetization yoke was fabricated to magnetize the steel plate specimen and measure the magnetic flux leakage signal. In order to remove the noise and increase the resolution of the image in the signal collected from the hall sensor, various of signal processing was performed. P-P value was analyzed for each channel to analyze the magnetic flux leakage signals measured from each damaged part. Based on the above processed signals and analysis, it was converted into heatmap image. Through this, it was possible to identify the damage on the steel plate at glance by imaging magnetic flux leakage signal.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.2
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• pp.110-115
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• 2010

This study was conducted to estimate the feasibility using thermal image measurement that is applicable to internal leak diagnosis for the power plant valve. Abnormal heating of valve surface associated with high temperature steam f10w toward valve outlet side in the condition of low temperature is a primary indicator of leakage problems in high temperature and pressure valves. Thermal imaging enables to see the invisible thermal radiation that may portend impending damage before their condition becomes critical. When steam flow in valve outlet side in the condition of low temperature is converted into heat transmitted through the valve body due to the internal leakage in valve. The existence of abnormally increasable leakage rate in the valve will result in abnormally high levels of heat to be generated that can be quickly identified with a thermal image avoiding energy loss or damage of valve component. From the experimental results, it was suggested that the thermal image measurement could be an effective way to precisely diagnose and evaluate internal leak situation of valve.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.4
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• pp.315-322
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• 2008

Valves in power plants are leaking internally by various damages including insertion of foreign objects on seat, seat crack, defects and fatigue crack of stem packing or welds etc. due to severe operating conditions such as high temperature and high pressure for extended period time. Acoustic emission(AE) technology should be applied in order to diagnose precisely and evaluate these valve internal leak. In this paper, results of studies which have accomplished in actual power plant are presented. We have analyzed background noise, AE signal level and frequency spectrum through laboratory tests on the basis of various actual conditions in power plant, and also have considered evaluation methods on the background noise, AE properties and the detectable minimum leak rate according to valve leak conditions through comparing with results of field tests in power plant. As a result of these studies, we conformed that evaluation of internal leak conditions including discrimination of leak or not, and the detectable minimum leak rate is possible, and also it is expected to contribute to safe operation and prevention of energy loss in power plants.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.2046-2047
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• 2008

본 논문에서는 가공 배전선로에 사용되고 있는 피뢰기의 상태 진단을 위한 누설전류 분석기법에 대해 기술하였다. 현장에서 다양한 환경 스트레스를 받고 있는 피뢰기는 점차 열화가 진행되어 선로 고장의 원인이 되므로 이를 사전에 검출하여 고장을 예방하는 것이 중요하다. 피뢰기 이상을 효과적으로 검출하는 방법의 하나로 사용되고 있는 누설전류 측정방법에 대해 평가하였다. 피뢰기 누설전류는 측정 환경에 영향을 받을 수 있기 때문에 현장 측정한 결과와 실험실에서 측정한 결과를 비교하여 분석하여 환경영향을 보정하여 판단하는 방법을 고려하였다. 또한 온도에 따른 누설전류 값의 변화를 분석하여 누설전류에 의한 피뢰기 상태 판단 근거를 마련하였다. 이를 위해 현장에서 설치 운용되고 있는 피뢰기를 지역별로 고르게 발취하여 측정 분석하였다.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.1
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• pp.45-51
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• 2004

Boiler tubes in power plants are often leaked due to various material degradations including creep and thermal fatigue damage under severe operating conditions such as high temperature and high pressure over an extended period of time. To monitor and diagnose the tubes on site and in real time, the acoustic emission (AE) technology was applied. We developed an AE leak detection system, and used it to study the variation of AE signal from the on-site tubes in response to the changes in the boiler operation condition and to detect the locations of leakage based on it. Detection of leak was performed by acquiring and evaluating the signals in separate regimes of high and low frequency signal. As a result of these studies, we found that on-line monitoring and detection of leak location for boiler tubes is possible using the developed system. Thus, the system is expected to contribute to the safe operation of power plants, and prevent economic losses due to potential leak.

• 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.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.9
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• pp.867-873
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• 2010

The failure of water-cooled generator stator windings as a result of insulation breakdown due to coolant water leaks and water absorption often occurs worldwide. Such failure can cause severe grid-related accidents as well as huge economic losses. More than 50% of domestic generators have been operated for over 15 years, and therefore, they exhibit signs of aging. Leaking and water-absorbing windings are often found during an overhaul. In an existing method for evaluating the integrity of generator stator windings, the drying process of the interior of the windings is ignored and only final leak tests are performed. In this study, it is shown that water leaks and water absorption in stator windings can be detected indirectly through vacuum pattern analysis in the vacuum drying mode, which is the used in the preparation stage of the leak test.

• Journal of Korean Society of Disaster and Security
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• v.11 no.2
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• pp.53-60
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• 2018

To diagnosis the local damages of the steel plates, magnetic flux leakage (MFL) method that is known as a adaptable non-destructive evaluation (NDE) method for continuum ferromagnetic members was applied in this study. To analysis the sensitivity according to thickness of steel plate in MFL method based damage diagnosis, several steel plate specimens that have different thickness were prepared and three depths of artificial damage were formed to the each specimens. To measured the MFL signals, a MFL sensor head that have a constant magnetization intensity were fabricated using a hall sensor and a magnetization yoke using permanent magnets. The magnetic flux signals obtained by using MFL sensor head were improved through a series of signal processing methods. The capability of local damage detection was verified from the measured MFL signals from each damage points. And, the peak to peak values (P-P value) extracted from the detected MFL signals from each thickness specimen were compared each other to analysis the MFL based local damage detection sensitivity according to the thickness of steel plate.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.628-630
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• 2005

본 논문에서는 정상적으로 가동 중인 발전소에서 운전되는 기기들의 유량 변화 시 발생되는 음향신호를 분석하고 또 유량의 누설과 비누설시의 음향 변화를 분석하여 누설탐지의 가능성을 보였다.