• Proceedings of the Korean Nuclear Society Conference
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• 2005.10a
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• pp.991-992
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• 2005

• Journal of Korea Multimedia Society
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• v.15 no.1
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• pp.115-130
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• 2012

These days, most of safety-critical systems, which are systems those failures or malfunction may result in death or serious injury to people, or loss or severe damage to social systems, or environmental harm, are being built of embedded software or loaded controlling software systems on computers, electrical and electronic components or devices. There are a lot kind of fault analysis methods to evaluate safety of the safety-critical systems equipped computers, electrical and electronic components or devices with software. However, the only assessment method to evaluate software safety of a safety-critical system is not enough to analysis properly on account of the various types and characteristic of software systems by progress of information technology. Therefore, this paper proposes the integrated evaluation method and carries out a case study for the software safety of safety-critical system which embedded or loaded software sizes are small and control response times are not sensitive by use of two security analysis methods which are Fault Tree Analysis (FTA) and Fault Modes and Effect Analysis (FMEA) for ubiquitous healthcare system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.654-662
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• 2016

As the number of gates and basic events in fault trees increases, it becomes difficult to calculate the exact probability of the top event. In order to overcome this difficulty the BDD methodology can be used to calculate the exact top event probability for small and medium size fault trees in short time. Fault trees are converted to BDD by using CUDD library functions and a failure path search algorithm is proposed to calculate the exact top event probability. The backward search algorithm is more efficient than the forward one in finding failure paths and in the calculation of the top event probability. This backward search algorithm can reduce searching time in the identification of disjoint failure paths from BDD and can be considered as an effective tool to find the cut sets and the minimal cut sets for the given fault trees.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.5
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• pp.110-123
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• 1994

The development of automatic production systems have required inteligent diagnostic and monitoring function to repair system failure and reduce production loss by the failure. In order to perform accurate functions of intelligent system, inferencing about total system failure and fault analysis due to each mechanical component failures are required. Also the solution about repair and maintenance can be suggested from these analysis results. As an essential component of mechanical system, a bearing system is investigated to define the failure behavior. The bearing failure is caused by lubricant system failure, metallurgical defficiency, mechanical condition(vibration, overloading, misalignment) and environmental effect. This study described roller bearing fault train due to stress variation and metallurgical defficiency from lubricant failure by using FTA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.7 no.1
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• pp.18-24
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• 1982

The Tree phenomenon of the PMMA resin depends on an annex of the inorganic fillers and water. If the internal of an arganic insulating materials exist the fault of inorganic fillers, Void and Projecting part, the high voltage concentrates in this place. It leaves a trace about the partical breakdown and this phenomenon develops into the degration of insulating material. This paper researchses that have an effect on the tree phenomenon by the inorganic fillers and water. The results is as follow. (1) The growth of tree are less the influence of inorganic fillers. Because , the constant of water are more. (2) If the tree branches contact the inorganic filler, the advance are relaxation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1507-1515
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• 2008

It is essential for electric power companies to have a quick restoration system of the faulted pole transformers which occupy most of transformers to supply stable electricity. However, it takes too much time to restore it when a transformer is out of order suddenly because we now count on operator in investigating causes of failure and making decision of recovery methods. This paper presents the concept of 'Fault pattern analysis and Restoration prediction model using Data mining techniques’, which is based on accumulated fault record of pole transformers in the past. For this, it also suggests external and internal causes of fault which influence the fault pattern of pole transformers. It is expected that we can reduce not only defects in manufacturing procedure by upgrading quality but also the time of predicting fault patterns and recovering when faults occur by using the result.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.533-543
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• 2022

Purpose: The purpose of this study is to identify and resolve the causes of defects in the unmanned aerial vehicle launch system(propulsion wire fracture, rear rail deformation) and to prevent recurrence. Methods: The causes of the two defects were derived through fault tree analysis for each of the two defects and fault reproduction tests. In the case of propulsion wire, the installation of a high speed camera to check the behavior of wire was the driving force behind the defect resolution. Results: The results of this study are as follows; It was determined that the thickness of the washer was less than the maximum tolerance of the pulley was the cause of the propulsion wire fracture defect. Failure to comply with the launch procedure and insufficient safety margin were judged as the cause of the rear rail deformation defect. Accordingly, the configuration was changed to remove each defect. Conclusion: The case of this study was conducted to eliminate defects in the launch system for UAV. The causes of defects were estimated through fault tree analysis. After the configuration change, Structural analysis and launch tests were performed to demonstrate the safety and effectiveness of the modified configuration. As a result, the effect of the modified configuration was verified.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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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.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.199-202
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• 2001

In this paper, we proposed and analyzed a new class of irregular fault-tolerant multistage interconnection network named as Extended-QT(Quad Tree) network. E-QT network is extended QT network. A unique path MIN usually is low hardware complexity and control algorithm. So we proposes a class of multipath MIN which are obtained by adding self-loop auxiliary links at the a1l stages in QT(Quad Tree) networks so that they can provide more paths between each source-destination pair. The routing of proposed structure is adaptived and is based by a routing tag. Starting with the routing tag for the minimum path between a given source-destination pair, routing algorithm uses a set of rules to select switches and modify routing tag. Trying the self-loop auxiliary link when both of the output links are unavailable. If the trying is failure, the packet discard. In simulation, an index of performance called reliability and cost are introduced to compare different kinds of MINs. As a result, the prouosed MINs have better capacity than 07 networks.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 2000.11a
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• pp.390-395
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• 2000

화학공정에서 발생하는 사고의 주요 원인으로는 조업자의 실수, 장치고장, 안전장치의 미비, 운전조건의 이상을 들 수 있다. 화학공정의 위험 분석은 HAZOP, FTA, ETA, 및 CA 등이 산업계에서 가장 유용하고 폭넓게 사용되고 있는 분석 방법이다. 이들 위험분석 기법 중에서 FTA(Fault Tree Analysis)는 사고의 세부적인 원인목록을 작성하여 해당사고의 구조를 파악할 수 있으며 복잡한 시스템내의 결함을 최소시간과 최소비용으로 효과적으로 예방할 수 있게 하는 정량적 위험성 평가 방법이다. 일반적으로 이 방법들은 전문가 집단에 의해 수행되기 때문에 전문가 집단의 능력과 투여되는 시간에 많이 비례하여 왔던 것이 사실이다. 이러한 이유로 인하여 위험분석방법의 자동화가 절실히 대두되고 있는 실정이다.(중략)