• KEPCO Journal on Electric Power and Energy
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• 제8권2호
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• pp.93-96
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• 2022

The boiler tubes of thermal power plants are exposed to harsh environment of high temperature and high pressure, and the deterioration state of materials rapidly increases. In particular, parent material and welds of the materials used are subjected to a temperature change and various constraints, resulting in deformation and its growth, resulting in frequent leakage accidents caused by tube failure. The power plant checks the integrity of boiler tubes through non-destructive testing as it may act as huge costs loss and limitation of power supply during power station shutdown period due to boiler tube leakage. However, the current non-destructive testing is extremely limited in the field to detect micro cracks. In this study, the ability of metal magnetic memory technique to detect flaws of size that are difficult to inspect by the visual or general non-destructive methods was verified in the early stage of their occurrence.

• 전기학회논문지
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• 제66권10호
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• pp.1445-1453
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• 2017

In this paper, we propose a fault detection model based on multi-layer neural network using data mining technique for faults due to boiler tube leakage in a thermal power plant. Major measurement data related to faults are analyzed using statistical methods. Based on the analysis results, the number of input data of the proposed fault detection model is simplified. Then, each input data is clustering with normal data and fault data by applying K-Means algorithm, which is one of the data mining techniques. fault data were trained by the neural network and tested fault detection for boiler tube leakage fault.

• Journal of Electrical Engineering and Technology
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• 제11권4호
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• pp.848-859
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• 2016

System failures in thermal power plants (TPPs) can lead to serious losses because the equipment is operated under very high pressure and temperature. Therefore, it is indispensable for alarm systems to inform field workers in advance of any abnormal operating conditions in the equipment. In this paper, we propose a clustering-based fault detection method for steam boiler tubes in TPPs. For data clustering, k-means algorithm is employed and the number of clusters are systematically determined by slope statistic. In the clustering-based method, it is assumed that normal data samples are close to the centers of clusters and those of abnormal are far from the centers. After partitioning training samples collected from normal target systems, fault scores (FSs) are assigned to unseen samples according to the distances between the samples and their closest cluster centroids. Alarm signals are generated if the FSs exceed predefined threshold values. The validity of exponentially weighted moving average to reduce false alarms is also investigated. To verify the performance, the proposed method is applied to failure cases due to boiler tube leakage. The experiment results show that the proposed method can detect the abnormal conditions of the target system successfully.

• Corrosion Science and Technology
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• 제18권2호
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• pp.55-60
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• 2019

Corrosion failure in the convection part of peak load boiler (PLB) of the district heating system led to water leakage. Herein, Internal Rotary Inspection System (IRIS) inspection was employed to examine wall thinning and the cause of leakage in the flue tube. The corrosive products of the turbulator and tube were investigated using scanning electron microscope combined with energy dispersive spectroscopy, X-ray diffraction, and inductively coupled plasma (ICP). Majority of the serious corrosion damage was observed near the turbulator located in the upper flue tube. ICP analysis of the boiler water revealed oxide formation of sodium chloride in the lower end part of the flue tube. A cross-sectional view of the turbulator revealed the presence of double-layers of the oxide film, indicating environmental change during operation associated with water leakage. The outer surface of the turbulator consisted of the acid oxides such as $NO_x$ and $SO_x$ along with sodium and chloride ions. Dew-point corrosion is hypothesized as the main cause for the formation of acid oxides in the region of contact of the flue tube and the turbulator.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 춘계학술대회논문집
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• pp.172-175
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• 2008

In the last five years, 45 people died and 104 were wounded because of carbon monoxide poisoning accident. CO poisoning accident is higher than any other gas accident in the rate of deaths/incidents. Most of these CO poisoning accidents were caused by defective exhaust tube in the old gas boiler and multi-use facility. In this study, the spread of CO gas released from leakage hole of exhaust tube was analyzed by computational flow modeling and concentration measuring test. CO gas leaked form exhaust tube in a building was highest concentrated near the ceiling and formed the circular currents along the walls. Through these experiments and simulation, the reasonable installation location of CO alarm was made certain and suggested.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회B
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• pp.2868-2873
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• 2008

Carbon Monoxide(CO) poisoning accident is higher than any other gas accident in the rate of deaths/incidents. In the last five years, 36 people died and 104 were wounded because of carbon monoxide poisoning accident. Most of these CO poisoning accidents were caused by defective exhaust tube in the old gas boiler and multi-use facility. In this study, the spread of incomplete combustion gas(CO) released from leakage hole of exhaust tube was analyzed by computational flow modeling and concentration measuring test. CO gas leaked form exhaust tube in a building was highest concentrated near the ceiling and formed the circular currents along the walls. Through these experiments and simulation, the reasonable installation location of carbon monoxide alarm was made certain and suggested.

• 비파괴검사학회지
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• 제36권3호
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• pp.181-187
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• 2016

화력발전용 보일러 내부에는 연소열을 고온 고압의 스팀으로 변환하기 위한 열교환 튜브가 복잡한 형태로 배치되어 있다. 이 튜브에서 누설이 발생할 경우 고압의 스팀에 의해 치명적인 고장과 발전 정지를 초래하며, 누설 발생 여부를 조기에 검출하지 못할 경우 인근 튜브의 손상까지 연쇄적으로 발생하여 조기에 튜브 누설을 검출할 수 있는 기술 확립이 필요하다. 본 논문에서는 기존 보일러 튜브 누설 감시 설비(BTLD)에 음향방출(AE) 기술을 적용하여 기존 시스템 대비 미세누설을 검출하고 조기에 경보를 발생시킬 수 있는 시스템에 대해 개발을 하였다. 또한 이 시스템을 검증하기 위해 실제 운전 중인 560 MW급 화력발전소 보일러에서 다양한 크기(ⵁ2, ⵁ5, ⵁ10 mm)의 모의 누설시험을 실시하였으며, 그 결과 기존 시스템에서는 검출하지 못하였던 미세누설(ⵁ2 mm, ⵁ5 mm)에 대해 개발된 시스템은 조기에 경보를 발생(18 dB 이상 신호 상승)시킬 수 있음을 확인하였다.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2009년도 추계학술발표대회 논문집
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• pp.259-264
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• 2009

Most of the fossil power plants firing lower grade coals are challenged with maintaining good combustion conditions while maximizing generation and minimizing emissions. In many cases significant derate, availability losses and increase in unburned carbon levels can be attributed to poor combustion conditions as a result of poorly controlled local fuel and air distribution within the boiler furnace. The poor combustion conditions are directly related to the gas flow deviation in upper furnace and convection tube-bank but a less reported issue related to in large-scale oppose wall fired boilers. In order to develop a on-line combustion monitoring system and suggest an alternative heat flux estimation method at tube bank, which is very useful information for boiler design tool and blower optimizing system, field test was conducted at operating power boiler. During the field test the exhaust gases' temperature and tube metal temperature were monitored by using a spatially distributed sensors grid which located in the boiler's high temperature vestibule region. At these locations. the flue gas flow is still significantly stratified, and air in-leakage is minimal which enables tracing of poor combustion zones to specific burners and over-fire air ports. Test results showed that the flue gas monitoring method is more proper than metal temperature distribution monitoring for real time combustion monitoring because tube metal temp. distribution monitoring method is related to so many variables such as flue gas, internal flow unbalance, spray etc., Heat flux estimation at the tube bank with flue gas temp. and metal temp. data can be alternative method when tube drilling type sensor can't able to use.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2018년도 제58차 하계학술대회논문집 26권2호
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• pp.55-56
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• 2018

화력발전소의 중요 구성품인 보일러 튜브의 예기치 못한 누설 사고로 인해 수억원에 해당하는 손실이 발생하고 있다. 본 논문에서는 보일러 튜브의 누설 감지를 위해 유전 알고리즘을 이용하여 추출 가능한 특징들 중 누수 감지에 유용한 특징들을 선택하고, 선택된 특징으로 서포트 벡터 머신을 이용하여 보일러 튜브의 누설 감지하는 방법을 제안한다. 이는 뛰어난 성능을 보였으며, 향후 본 기술을 이용하면 발전소의 손실 예방에 크게 도움이 될 것으로 기대된다.

• 한국지능시스템학회논문지
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• 제26권3호
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• pp.246-252
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• 2016

화력발전소의 설비들은 매우 높은 온도와 압력의 환경에서 운전되므로, 설비고장은 상당한 인적 물적 손실로 이어진다. 그러므로 발전설비의 비정상정인 동작 상태를 사전에 확인할 수 있는 고장탐지 시스템이 필수적이다. 본 연구에서는, 화력발전소 증기보일러의 고장탐지를 위해서 마할라노비스 거리(Mahalanobis distance, MD)를 이용하였다. MD 기반의 고장탐지방법에서는, 비정상샘플은 정상샘플들로부터 멀리 떨어져 있다고 가정한다. 정상상태로 동작중인 대상시스템으로부터 수집된 다변량 샘플을 이용하여 평균벡터와 공분산행렬을 계산하고, MD값의 문턱값을 설정한다. 검증단계에서는, 평균벡터와 검증샘플들 간의 MD를 구한 후, 계산된 MD 값이 미리 설정된 문턱값보다 높으면 알람신호가 발생하게 된다. MD 기반의 고장탐지방법의 성능을 검증하기 위해서, 200MW 유연탄 화력발전소의 증기보일러 튜브누설로 인해서 발전정지 된 사례를 사용하였다. 실험결과는 MD 기반의 고장탐지기법이 발전정지가 발생하기 이전의 이상징후를 성공적으로 탐지할 수 있음을 보여준다.