• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.952-954
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• 1998

This paper presents an artificial neural network approach to diagnose and detect faults in oil-filled power transformers based on dissolved gas analysis. The proposed algorithm is used to detect faults with or without cellulose involved. Several neural network topologies have been considered. Good diagnosis accuracy is obtained with the proposed approach.

• Journal of the Korean Society of Safety
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• v.26 no.4
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• pp.41-46
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• 2011

The purpose of this paper is to analyze the causes of accidents related to the 3 phase 170 kV gas insulated switchgear of a power system collected from accident sites to secure data for the prevention of similar accidents and provide important points of view regarding diagnosis for the prevention of accidents involving gas insulated switchgears. The analysis results of the causes of accidents involving gas insulated switchgears showed deformation of the manipulation lever installed at the S-phase, disconnection of the insulation rod connection, melting of the upper conductor, a damaged tulip, damage to the lower spacer and the spacer at the breaker, etc. It is believed from this result that the potential for accidents has expanded due to accumulated energy as a result of repeated deterioration. The carbonization depth of a GIS was formed near the screw (T2, T3) used to secure the lower pole of the S-phase tulip. It is not known what has caused the screws to be extruded and melted. However, it is thought that an unbalanced electromagnetic force, micro-discharge, surface discharge, etc., have occurred at that point. In addition, even though 16 years have passed since its installation, there was no installation defect, act of arson, accidental fire, etc. General periodical inspection and diagnosis failed to find the factors causing the accidents. As a system contained in a closed metal container, it has a high risk factor. Therefore, it is necessary to design, install and operate a GIS in accordance with the standard operational procedure (SOP). In addition, it is necessary to apply conversion technology for periodical SF6 gas analysis and precision safety diagnosis. It is expected that tracking and managing these changes in characteristics by recording the results on the history card will provide a significant accident prevention effect.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.4
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• pp.194-199
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• 2017

Power transformers are an important factor for power transmission and cause fatal losses if faults occur. Various diagnostic methods have been applied to predict the failure and to identify the cause of the failure. Typical diagnostic methods include the IEC diagnostic method, the Duval diagnostic method, the Rogers diagnostic method, and the Doernenburg diagnostic method using the ratio of the main gas. However, each diagnostic method has a disadvantage in that it can't diagnose the state of the power transformer unless the gas ratio is within the defined range. In order to solve these problems, we propose a diagnosis method using ELM based intelligent algorithm and fuzzy membership function. The final diagnosis is performed by multiplying the result of diagnosis in the four diagnostic methods (IEC, Duval, Rogers, and Doernenburg) by the fuzzy membership values. To show its effectiveness, the proposed fault diagnostic system has been intensively tested with the dissolved gases acquired from various power transformers.

• Journal of the Korean Institute of Gas
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• v.4 no.4 s.12
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• pp.42-49
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• 2000

Due to their size and complexity, it is very difficult to make diagnostic system for the whole chemical processes. Therefore, a systematic approach is required to decompose larpge-scale process into sub-processes and then diagnose them. This paper suggests a method for the minimization of knowledge base and flexible diagnosis to be used in qualitative fault diagnosis based on Fault-Effect Tree model. The system can be decomposed for flexible diagnosis, size reduction of knowledge base, and consistent construction of complex knowledge base. The new node, gate-variable, is introduced to connect the cause-effect relationships of each sub-process. For on-line diagnosis, off-line analysis is performed to construct Fault-Effect Trees of gate-variables as well as activation conditions of gate-variables. On-line diagnosis strategy is modified to get the same diagnosis result without system decomposition. The proposed method is illustrated with a fault diagnosis system for a large-scale boiler plant.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.539-543
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• 2009

This paper describes the sensitivity enhancement in measurement of the hydrogen gas dissolved in oil using gas collection time. On-line gas measurement is a useful for continuous monitoring of power transformer. Recently many studies on hydrogen gas measurement, due to their simplicity and low price, have been done for transformer monitoring. In measurement of the hydrogen gas in oil, the suitable sensitivity and resolution in the desired ranges of the gas concentrations are needed for the reliable monitoring of power transformers. In this study, the sensor output trends were analyzed with the hydrogen gas collection time which means the time to collect the hydrogen gas before reaction of hydrogen gas sensor. It is indicated that the sensor outputs were increased with the increase of hydrogen gas collection times at the same hydrogen gas concentrations.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.1165-1168
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• 2017

This paper suggests a fault diagnosis of damage on inner liner of regeneratively-cooled combustion chamber during gas generator cycle rocket engine hot firing test. This method focuses on a phenomenon that fuel flow rate difference between two flow estimate methods changes under an inner liner damage of combustion chamber causing fuel leakage and it is expected that it contributes to detect a damage on the combustion chamber in early stage and prevent further destruction during the hot firing test.

• Journal of Veterinary Clinics
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• v.37 no.4
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• pp.231-234
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• 2020

An 11-year-old, 4.3 kg, mixed breed, intact female dog exhibiting vomiting and a reduced appetite was presented. On physical examination, palpation of the right kidney elicited discomfort. Blood analysis revealed leukocytosis with neutrophilia, and elevation of alkaline phosphatase and blood urea nitrogen. Escherichia coli was detected in urine culture, whereas urine analysis showed absence of glucose. Radiography and ultrasonography suggested that there was gas in the right renal parenchyma, and computed tomography was performed while the dog was awake to investigate the suspected gas in the right kidney. After unilateral ureteronephrectomy, a histological diagnosis of right emphysematous pyelonephritis (EPN) was made. EPN refers to a severe necrotizing infection of the renal parenchyma with gas accumulation in the tissue. It is rare in both human and veterinary medicine, and almost all EPN patients have uncontrolled diabetes mellitus. This case report describes the imaging-based diagnosis of a rare occurrence of unilateral EPN in a non-diabetic dog.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.53-62
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• 2023

Due to the recent increase in new and renewable energy, gas turbine generators start and stop every day to supply high-quality power, and accordingly, the life span of high-temperature parts is shortened and the failure of combustion chamber temperature sensors increases. Therefore, in this study, we proposed a fuzzy logic-based failure diagnosis algorithm that can accurately diagnose and systematically detect the failure of the sensor when the dual temperature sensor used for gas turbine control fails, and to confirm the usefulness of the proposed algorithm We tried to confirm the usefulness of the proposed algorithm by performing various simulations under the matlab/simulink environment.

• Proceedings of the KIEE Conference
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• 2004.07c
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• pp.1860-1862
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• 2004

It is widely known that the ultra high frequency (UHF) method that detects the electromagnetic wave of the PD pulses in the gas insulated space is one of the most competitive methods for its high sensitivity. From the above point of view, this paper describes the characteristics of GIS PD signals measured with ultra wide band (UWB) GIS PD detecting system in which PD signals are detected into the dual UHF band. The UWB PD detection system consists of the UWB UHF coupler, the UWB low noise amplifier (LNA) and the oscilloscope. The dual bands for PD signals are 0.5-2GHz(full band) and 1-2GHz(high band). As results, it was found that the partial discharges of each defect have their own characteristic pattern and the ratio of High band to Full band increases with gas pressure.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.413-416
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• 2007

If obstacle in GIS(Gas Insulted Switchgear), its affects are great are on the community and it is consequently demanded lots of difficulities to recover and repair. Accordingly, diagnosis techniques, that are able to prevent from accidents before they happen by providing more stable and highly reliable power effectively and finding sign of the accidents is very important. The strip-senser measured impedance bandwidth of the proposed antenna is from 0.5[GHz] to 2.5[GHz] with the stop band from 0.5[GHz] to 1.7[GHz] for VSWR<2. The antenna is will play an important role for the senser for insulation diagnosis system by UHF method of real site GIS and power equipment using $SF_6$ gas.