• Fire Science and Engineering
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• v.31 no.6
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• pp.67-73
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• 2017

An aircraft maintenance hangar is a building that stores, maintains, and inspects expensive aircraft. The frequency of fire occurrence is low, but the resulting human and material damage can be very serious. Therefore, in this study, we conducted a qualitative analysis of the fire safety of the currently operating fire suppression systems for aircraft maintenance hangars using the Fault Tree method, and then performed a quantitative analysis using the failure rate data for the derived basic events and analyzed the importance of the minimal cut sets. As a result of the qualitative analysis by the minimal cut set, it was found that there were 14 accident paths that could be expanded to a large fire, due to the fire control failure of the aircraft hangar fire suppression system. The quantitative analysis revealed that, the probability of the fire expanding into a large one is $2.08{\times}E-05/day$. The analysis of the importance of the minimal cut set shows that four minimal cut sets, namely the fire detector and foam head action according to the zone and blocking of the foam by the aircraft wing and the fire plume, had the same likelihood of causing the fire to develop into a large one, viz. 24.95% each, which together forms the majority of the likelihood. It was confirmed for the first time by fault tree method that the fire suppression system of aircraft maintenance hangars is not suitable for fires under the aircraft wings and needs to be improved.

• Journal of the Korean Society of Safety
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• v.18 no.2
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• pp.64-72
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• 2003

A new reliability assessment methodology is presented and the new method is compared with fault tree analysis. The system is modeled by directed graph at a new methodology, which is composed of nodes and arcs. The directed graph corresponds to the layout of chemical process and is easy to construct. Therefore, the directed graph analysis is applicable to the chemical process that has complex sequence. The example of fault tree analysis and directed graph analysis is given. The directed graph analysis has proved to be a valuable and useful method for the reliability assessment of chemical process.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.407-410
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• 2006

Decision tree is one of the most effective and widely used methods for building classification model. Researchers from various disciplines such as statistics, machine teaming, pattern recognition, and data mining have considered the decision tree method as an effective solution to their field problems. In this paper, an application of decision tree method to classify the faults of induction motors is proposed. The original data from experiment is dealt with feature calculation to get the useful information as attributes. These data are then assigned the classes which are based on our experience before becoming data inputs for decision tree. The total 9 classes are defined. An implementation of decision tree written in Matlab is used for four data sets with good performance results

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.105-112
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• 2006

The main function of a reactor protection system is to maintain the reactor core integrity and the reactor coolant system pressure boundary. Generally, the reactor protection system adopts the 2-out-of-m redundant architecture to assure a reliable operation. This paper describes the safety assessment of a digital reactor protection system using the fault tree analysis technique. The fault tree technique can be expressed in terms of combinations of the basic event failures such as the random hardware failures, common cause failures, operator errors, and the fault tolerance mechanisms implemented in the reactor protection system. In this paper, a prediction method of the hardware failure rate is suggested for a digital reactor protection system, and applied to the reactor protection system being developed in Korea to identify design weak points from a safety point of view.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.457-462
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• 1995

This paper describes diagnosis strategy of the Flexible Multiple Fault Diagnosis Module for forecasting faults in system and deciding current machine state form sensor information. Most studydeal with diagnosis control stategy about single fault in a system, this studies deal with multiple fault diagnosis. This strategy is consist of diagnosis control module such as backward tracking expert system shell, various neural network, numerical model to predict machine state and communication module for information exchange and cooperate between each model. This models are used to describe structure, function and behavior of subsystem, complex component and total system. Hierarchical structure is very efficient to represent structural, functional and behavioral knowledge. FT(Fault Tree). ST(Symptom Tree), FCD(Fault Consequence Diagrapy), SGM(State Graph Model) and FFM(Functional Flow Model) are used to represent hierachical structure. In this study, IA(Intelligent Agent) concept is introduced to match FT component and event symbol in diagnosed system and to transfer message between each event process. Proposed diagnosis control module is made of IPC(Inter Process Communication) method under UNIX operating system.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.822-829
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• 2022

According to existing study into the remote fault diagnosis procedure, the current diagnostic approach has an imperfect decision model, which only supports communication in a close distance. An Internet of Things (IoT)-based remote fault diagnostic approach for wind power equipment is created to address this issue and expand the communication distance of fault diagnosis. Specifically, a decision model for active power coordination is built with the mechanical energy storage of power generation equipment with a remote diagnosis mode set by decision tree algorithms. These models help calculate the failure frequency of bearings in power generation equipment, summarize the characteristics of failure types and detect the operation status of wind power equipment through IoT. In addition, they can also generate the point inspection data and evaluate the equipment status. The findings demonstrate that the average communication distances of the designed remote diagnosis method and the other two remote diagnosis methods are 587.46 m, 435.61 m, and 454.32 m, respectively, indicating its application value.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.10
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• pp.516-523
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• 2000

In this paper, intelligent methods using digital protective relay in power supervisory control system is developed in order to protect power systems by means of timely fault detection and diagnosis during operation for induction motor which has various load environments and capacities in power systems. The spectrum pattern of input currents was used to monitor to state of induction motors, and by clustering the spectrum pattern of input currents, the newly occurrence of spectrums pattern caused by faults were detected. For diagnosis of the fault detected, the fuzzy fault tree was derived, and the fuzzy relation equation representing the relation between an induction motor fault and each fault type, was solved. The solution of the fuzzy relation equation shows the possibility of each fault's occurring. The results obtained are summarized as follows: 1) The test result on the basis of KEMC1120 and IEC60255, show that the operation time error of the digital motor protective relay is improved within ${\pm}5%$. 2) Using clustering algorithm by unsupervisory learning, an on-line fault detection method, not affected by the characteristics of loads and rates, was implemented, and the degree of dependency by experts during fault detection was reduced. 3) With the fuzzy fault tree, fault diagnosis process became systematic and expandable to the whole system, and the diagnosis for sub-systems can be made as an object-oriented module.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1529-1532
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• 2007

Failure Mode, Effects, and Criticality Analysis (FMECA) is an extension of FMEA which includes a criticality analysis. The criticality analysis is used to chart the probability of failure modes against the severity of their consequences. The result highlights failure modes with relatively high probability and severity of consequences, allowing remedial effort to be directed where it will produce the greatest value. However, there are several limitations. Measuring severity of failure consequences is subjective and linguistic. Since The result of FMECA only gives qualitative and quantitative informations, it should be re-analysed to prioritize critical units. Fuzzy set theory has been introduced by Lotfi A. Zadeh (1965). It has extended the classical set theory dramatically. Based on fuzzy set theory, fuzzy logic has been developed employing human reasoning process. IF-THEN fuzzy rule based assessment approach can model the expert's decision logic appropriately. Fault tree analysis (FTA) is one of most common fault modeling techniques. It is widely used in many fields practically. In this paper, a simple fault tree analysis is proposed to measure the severity of components. Fuzzy rule based assessment method interprets linguistic variables for determination of critical unit priorities. An rail-way transforming system is analysed to describe the proposed method.

• The Journal of Information Systems
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• v.17 no.3
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• pp.25-37
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• 2008

In a fault tree analysis, an uncertainty importance measure is often used to assess how much uncertainty of the top event probability (Q) is attributable to the uncertainty of a basic event probability ($q_i$), and thus, to identify those basic events whose uncertainties need to be reduced to effectively reduce the uncertainty of Q. For evaluating the measures suggested by many authors which assess a percentage change in the variance V of Q with respect to unit percentage change in the variance $v_i$ of $q_i$, V and ${\partial}V/{\partial}v_i$ need to be estimated analytically or by Monte Carlo simulation. However, it is very complicated to analytically compute V and ${\partial}V/{\partial}v_i$ for large-sized fault trees, and difficult to estimate them in a robust manner by Monte Carlo simulation. In this paper, we propose a method for evaluating the measure using discretization technique and Monte Carlo simulation. The proposed method provides a stable uncertainty importance of each basic event.

• Journal of the Earthquake Engineering Society of Korea
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• v.13 no.2
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• pp.47-58
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• 2009

In this study, a seismic fragility analysis was performed for substation systems in Korea. To evaluate the seismic fragility function of the substation systems, a fragility analysis of the individual equipment and facilities of the substation systems was first performed, and then all systems were considered in the fragility analysis of the substation systems using a fault-tree method. For this research, the status of the substation systems in Korea was investigated for the classification of the substation systems. Following the classification of the substation systems, target equipment was selected based on previous damage records in earthquake hazards. The substation systems were classified as 765kV, 345kV, and 154kV systems. Transformer and bushing were chosen as target equipment. The failure modes and criteria for transformer and bushing were decided, and fragility analysis performed. Finally, the fragility functions of substation system were evaluated using the fault tree method according to damage status.