• 대한기계학회논문집A
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• 제29권7호
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• pp.947-954
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• 2005

The purpose of this study is to develop failure pressure evaluation models, which are applicable to straight pipes and elbows containing an internally wall thinning defect induced by flow-accelerated-corrosion (FAC). In this study, thus, three dimensional finite element (FE) analyses are performed to investigate the dependences of failure pressure of internally wall thinned pipe on the defect shape, the pipe geometry, and the defect location and bend radius of elbow. Also, the existing failure pressure assessment models for externally wall thinned pipes are examined. Based on these, the new models for assessing failure pressure of piping components with an internally wall thinning defect are proposed. Comparison of failure pressure, predicted by proposed models, with FE analysis result shows good agreement regardless of pipe type, defect shape, and defect location and bend radius.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2000년도 추계학술대회
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• pp.269-277
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• 2000

The component reliability database is required in PSA (Probabilistic Safety Analysis) for NPP (Nuclear Power Plant). We have applied a generic database to the PSA for the Korean NPPs, since there is no specific component reliability database. Therefore we are developing the plant-specific component reliability database for domestic NPPs. We also extend the experience and knowledge of PSA and component reliability database for NPP to chemical industry We collect the raw data like component operation history and maintenance history and then input the required data for the component reliability database through failure analysis. With the database, we can not only perform PSA with real data but also perform maintenance optimization.

• 한국안전학회지
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• 제27권6호
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• pp.54-58
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• 2012

This paper is purposed to analyze electric leakage component which can prevent electrical fires on breaker capacity expansion and power failure by operation of ELB(Earth leakage breaker) for stable sizes. In order to analysis for electric leakage component for stable sizes, this paper studied field state investigation which are at stable companies( 10 companies) in cheong-won location to deduce the problems of electric leakage component is analyzed. The field state experiment method is measured with electric leakage component which load part of ELB detected by electric loads(electrical fan, lighting, auto waterer, feeder and halogen lighting) and stable sizes. Results show that electric leakage component suggested in this paper are valuable and usable to electrical fire in leakage current based on environment factor, which will prevent severe damage to human beings and properties and reduce the electrical fires in stable.

• 한국항해학회지
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• 제17권1호
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• pp.91-98
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• 1993

This paper presents a class of Bayes estimation of component steady-state availability . Throughout this paper, we will denote the mean time between failure and the mean time between repair by MTBF and MTBR respectively. In section 2 , we investigated Bayes estimation of the steady-state availability for noninformative prior density function and in section 3, we compute Bayes estimation for conjugate prior density function.

• 산업경영시스템학회지
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• 제40권1호
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.

• 유공압시스템학회논문집
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• 제3권3호
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• pp.8-13
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• 2006

It is very important for the manufacturers to predict the life of hydraulic system components according to the results of life tests. Since it takes too much time to test the hydraulic system components until failure, the no-failure test method is applied for the life test of them. If the shape parameter of Weibull distribution, the number of samples, the confidence level, and the assurance life are given, the no-failure test times of hydraulic system components can be calculated by given equation. Here, the procedures to obtain the no-failure test times of the hydraulic system components such as hydraulic motors and pumps, hydraulic cylinders, hydraulic valves, hydraulic accumulators, hydraulic hoses, and hydraulic filters are described briefly.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.326-327
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• 2011

Failure rate serves as a pivotal role in reliability study. When the system operates, failure datum of the system reflects the actual operating environment. Therefore, when we estimate the system's with the component failure data, we can find the more exact failure rate that reflected the system's operating environment. In this paper, we use the components' fault data and find out failure rate.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2011년도 춘계학술발표대회 논문집
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• pp.257-264
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• 2011

In this study, we performed sensitivity study of the $217Plus^{TM}$ system model to various parameters. Specific attention was put to logistics model and its behavior has been examined in terms of non-component failure causes. We first briefly explained the $217Plus^{TM}$ methodology with system level failure rate evaluation. We then applied experimental designs with several failure causes as factors. We used an orthogonal array with three levels of each parameter. Our results indicate that cannot duplicate, induced, and wear-out causes have dominant effects on the system failures and design, parts, and system management have much less but a little strong effects. The results in this study not only figure out the behavior of the predicted failure rate as functions of failure causes but provide meaningful guidelines for practical applications.

• 대한디지털의료영상학회논문지
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• 제16권1호
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• pp.61-67
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• 2014

The demand of cyclotron for PET (positron emission tomography) has rapidly grown as the more use of PET or PET-CT equipment requires the increased amount of radioactive isotopes for clinical positron emission. While research on failure statistics of medical equipment used in medical centers has continued to be done, the analysis and study on failure statistics of cyclotron have rarely been conducted. However, the growing demand shows the urgency of systematical management guideline and countermeasures for device failure to minimize any supply delay of radiopharmaceuticals occurred by such failure and complains from waiting patients for PET-CT diagnosis. Therefore, this study aims to analyze the failure report from Minitrace equipped in cyclotron which is owned by the department of nuclear medicine at Yeungnam University Medical Center and draws on the data to build effective management system for cyclotron.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 추계학술대회 논문집 전력기술부문
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• pp.272-274
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• 2003

Distribution system reliability evaluation estimates by approach methods such as Makove modelling or Monte Carlo simulation, equation of state and failure rate that is on one basic data used to these assessment technique is described as probability of average value. because average failure rate equipment device is aged as time goes by but there is shortcoming that such used failure rate does not evaluate thing which is correct in reliability change hereafter. In this paper, failure rate displayed that apply aging to basis equipment device by passing time using Weibull distribution one of life evaluation method and for express aging of component from utility's failure database.