• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.35-44
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• 2012

In the current maintenance system of building, safety inspection and precise safety diagnosis have been applied only for Type 1 and 2 buildings. Considering the fact that middle and small-size buildings take up 99.4% of total buildings, it is necessary to implement safety diagnosis for the buildings to make long lasting buildings. This study suggested improvement methods for adjusting the existing evaluation items to middle and small-size buildings by reviewing the current diagnosis system and a survey. Based on the methods, an improved model, which modified the existing diagnosis model, was developed by applying fuzzy theory. If the improved model of this study is applied on site, the buildings except Type 1 and 2 could be maintained constantly. In the future studies, it is necessary to implement the developed model practically, to strengthen the feasibility of the model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.474-477
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• 2002

Safety is very important to operate nuclear power plant. To guarantee the safety, nuclear power plant should be run without trouble. This paper presents the application of a failure diagnosis approach based on discrete event system theory to the pressurizer pressure control system for Pressurized Water Reactor. Also, this paper shows a scheme of failure diagnosis by distributed diagnoser.

• Journal of the Korean Society of Safety
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• v.7 no.4
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• pp.105-114
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• 1992

This paper presents an study on the knowledge based system for diagnosing the fire causes using the Fuzzy Possibility Measure( FPM ) about the electric-fire ignition. The Ignition values needed for causes diagnosis is computed as FPM for electric-fire ignition based on the internal scale technique that assigns numerically the characteristic difference of facts to the-tin-ear scale. For the convinience of inference, ignition sources are classified into seven types : short, ground fault, leakge of electricity, overcurrent, cord junction overheating, bad Insulation and spark. The system for causes diagnosis of electric-fire is composed of Knowledge Acquisition System, Inference Engine and Man-Machine Interface, The diagnosis system is wrritten in an artificial intelligence langusge “PROLOG” which uses depth-first search and backward chaining schemes in reasoning process.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.3
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• pp.160-167
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• 2018

In this paper, a black box, which is provided the reliability and user safety of home battery energy storage system connected with solar energy generation, is developed. In the developed scheme, a status and diagnosis data of battery management system, power conditioning system, solar energy generation and grid is measured. This status and diagnosis data is stored and displayed in the developed black box. In addition, this status and diagnosis data is stored and displayed in a monitoring system and a smart phone of user. A performance evaluation of the developed black box is carried out using emulator of home battery energy storage system connected with solar energy generation. Consequently, the developed black box is proved its superiority of the reliability and user safety.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1295-1302
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• 2016

In this paper, a black box, which is provided the reliability and user safety of home battery energy storage system connected with solar energy generation, is developed. In the developed scheme, a status and diagnosis data of battery management system, power conditioning system, solar energy generation and grid is measured. This status and diagnosis data is stored and displayed in the developed black box. In addition, this status and diagnosis data is stored and displayed in a monitoring system and a smart phone of user. A performance evaluation of the developed black box is carried out using emulator of home battery energy storage system connected with solar energy generation. Consequently, the developed black box is proved its superiority of the reliability and user safety.

• Journal of the Korean Institute of Gas
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• v.21 no.5
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• pp.64-69
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• 2017

South Korea is the world's second-largest importer of LNG and possess about 70 tanks which are in operation by 2017. Thirty years as the design warranty period have exceeded since LNG storage tanks as the core facility of LNG industry were constructed in 1986. The LNG storage tank is under precision safety diagnosis from 2014 due to urban gas business act amendment. There is no criteria of condition evaluation for outer tank of LNG storage tank at the time of precision safety diagnosis. Through analysis of structural characteristic of LNG storage tank and civil structure condition evaluation standards, the criteria of condition evaluation for main members was developed. The criteria of objective condition evaluation can improve safety and reliability of LNG storage tank and suggest matenance criteria.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.3
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• pp.208-214
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• 2011

In this thesis, the partial discharge according to applied voltage and variations of cross-sectional area and length of the conductor related to general condition for using cable was measured in order to study degradation diagnosis for 2-Core cable of the PVC insulator used in industrial fields for other safety installations. Also the thermal degradation conditions under various installation circumstances of cables were studied by assuming degradation conditions with each different degradation rate (50%, 67%, 100%) such as variation in degradated temperature, thermal exposure time, normal state, partially degradated state and overall degradated state for thermal degradation diagnosis. The quantity of electric discharge (V-Q) according to applied voltage was measured for measurement of inception voltage and extinction voltage. The quantity of electric discharge and the number of electric discharge (Q-N) were measured with applied voltage kept constantly. In addition, pictures were taken using SEM (scanning electron microscope) to compare the surface of external insulator to degradated state of internal insulator according to thermal degradation temperature and also compare the surface of external insulator to degradated surface state of internal insulator according exposure time of cables to thermal stress.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1306-1313
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• 2018

The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2859-2870
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• 2022

Because nuclear power plants (NPPs) are safety-critical infrastructure, it is essential to increase their safety and minimize risk. To reduce human error and support decision-making by operators, several artificial-intelligence-based diagnosis methods have been proposed. However, because of the nature of data-driven methods, conventional artificial intelligence requires large amount of measurement values to train and achieve enough diagnosis resolution. We propose a graph neural network (GNN) based accident diagnosis algorithm to achieve high diagnosis resolution with limited measurements. The proposed algorithm is trained with both the knowledge about physical correlation between components and measurement values. To validate the proposed methodology has a sufficiently high diagnostic resolution with limited measurement values, the diagnosis of multiple accidents was performed with limited measurement values and also, the performance was compared with convolution neural network (CNN). In case of the experiment that requires low diagnostic resolution, both CNN and GNN showed good results. However, for the tests that requires high diagnostic resolution, GNN greatly outperformed the CNN.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.4
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• pp.190-195
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• 2006

In this paper, safety algorithm of transformer is introduced for the sake of MV/LV distribution customers by using fuzzy theory. The current-carrying capacity of transformer is usually determined by the maximum temperature at which the transformer is permitted to operate. Overload of transformer has an effect on transformer utilization rate and maximum temperature rises as well as maximum ambient temperature of insulating materials. Therefore, we proposed the safety algorithm considering the overload of transformer and ambient temperature in this paper. We introduced the correlational equations between each parameters using experimental data of IEEE std C57.91-1995, and deduced the result using fuzzy reasoning. We guessed the safety algorithm making a diagnosis for the safety status of oil-immersed transformer.