• Proceedings of the KIEE Conference
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• 1994.07b
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• pp.1526-1529
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• 1994

In hydro-generator, a groundwall insulation of stator windings gradually deteriorates due to mechanical, thermal, electrical and environmental stresses. These stresses combine to result in loose windings, delamination of the stator insulation and/or electrical tracking of the end winding, all of which can lead to stator insulation failures. Conventionally, off-line tests such as partial discharge measurement, DC/AC current test and ${\Delta}tan{\delta}$ test has been used for estimation of winding condition. However, off-line test requires large power supply and generator outage. In addition, major cause of insulation problems such as loose wedges and slot discharges may not be found with off-line diagnoses. This paper describes the on-line partial discharge measurement techniques in the generator stator windings. The experimental results from the UIAM #1 hydro-generator confirms a optimistic application of on-line generator diagnosis method as a reliable tool for evaluation of winding condition.

• 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.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.109-109
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• 2010

On-line partial discharge(PD) diagnostic system is the most prominent systems to diagnose insulation condition for the high voltage rotating machines. Partial discharge measuring system(PDMS) series with ceramic coupler(PD detecting sensor) installed hydro generator and high voltage motor have been measured the PD data for many years. The trend of PD magnitude in the on-line PD system increased for some machines. These machines showed a same result in the conventional off-line PD test and PD magnitude decreased after stator winding insulation cleaning. This case study show that PDMS has been proved to be good results by comparing PD magnitude with on-line and off-line PD test and it is important to plan the maintenance project for the hydro generator stator winding because PD value was decreased after insulation cleaning.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.1
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• pp.62-67
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• 2005

Recently, polymer insulators that are used for high voltage applications have some advantages such as light weight, small size, vandalism resistance, hydrophobicity and easy making process. During outdoor service of polymer insulators, the surface of the insulating material is frequently subjected to moisture and contamination that lead to dry band arcing. Their tracking resistance, erosion resistance, end sealing and shed design are very important because dry band arcing causes degradation of polymer surface. Aging test to estimate life property of polymer insulator is executed through several international standard such as IEC 61109 and CEA tracking wheel test, but is not getting clear conclusion yet. There are two methods in the diagnosis method of polymer insulator such as off-line and on-line. The diagnosis methods in off-line are external condition analysis by the eye, contaminant analysis on surface, surface analysis, pollution withstand voltage test, power frequency flashover voltage test, lightning impulse flashover test, tensile fracture load test and flexural load test. Polymer material is also investigated it's tracking resistance by adding surface active agent in IEC 587. In this paper, the tracking performance of polymer insulator with salt solution which is added surface active agent. The diagnosis of insulator sample has been analyzed by leakage current and visual examination, STRI guide and thermal image camera.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.8
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• pp.766-771
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• 2005

In this study, PD(partial discharge) signals which occur at stator coil of traction Motor are acquired these data are used for classifying the PD sources. NN(neural network) has recently applied to classify the PD pattern. The PD data are used for the learning process to classify PD sources. The PD data come from normal specimen and defective specimens such as internal void discharges, slot discharges and surface discharges. PD distribution parameters are calculated from a set of the data, which is used to realize diagnostic algorithm. NN which applies distribution parameters is useful to classify the PD patterns of defective sources generating in stator coil of traction motor.

• Journal of Electrical Engineering and Technology
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• v.6 no.1
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• pp.111-118
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• 2011

In recent years, various types of partial discharge (PD) methods such as capacitive, inductive, electromagnetic, and acoustic coupling techniques have been developed for diagnosing rotating machines. An electromagnetic (EM) probe, which is an inductively coupled type of sensor, is required for detecting corona and internal discharges during off-line tests. In this study, a new technique for enhancing the measurement sensitivities for corona and internal discharge based on an EM inductive position sensor is proposed. An EM probe that winds wires around horseshoe-shaped and cylindershaped ferrites as helices is designed and optimized for the implementation of off-line PD monitoring of the stator winding of a rotating machine. The measurement system based on this design is implemented, and it is verified from the results of the experiment performed in this study that the probe provides similar performance as existing commercial products.

• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.3
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• pp.138-142
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• 2005

In this paper, we compared recognition rates between NN(neural networks) and clustering method as a scheme of off-line PD(partial discharge) diagnosis which occurs at the stator coil of traction motor. To acquire PD data, three defective models are made. PD data for classification were acquired from PD detector. And then statistical distributions are calculated to classify model discharge sources. These statistical distributions were applied as input data of two classification tools, BP(Back propagation algorithm) and ANFIS(adaptive network based fuzzy inference system) pre-processed FCM(fuzzy c-means) clustering method. So, classification rate of BP were somewhat higher than ANFIS. But other items of ANFIS were better than BP; learning time, parameter number, simplicity of algorithm.

• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.6
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• pp.223-227
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• 2005

Insulation failure of traction motor stator coil depends on the continuous stress imposed on it and knowing its insulation condition is an issue of significance for proper safety operation. In this paper, application of the NN (Neural Network) as a scheme of the off-line PD (partial discharge) diagnosis method that occurs at the stator coil of a traction motor was studied. For PD data acquisition, three defective models were made; internal void discharge model, slot discharge model and surface discharge model. PD data for recognition were acquired from a PD detector. Statistical distributions and parameters were calculated to perform recognition between model discharge sources. These statistical distribution parameters are applied to classify PD sources by the NN with a good recognition rate on the discharge sources.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.212-215
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• 2003

This paper presents constitution of a moderate price thermography system for on-line measurement. All objects with some temperature above absolute zero radiate in the infrared. The intensities and spectra of the infrared radiated from some object depend on the conditions and temperature distributions on the surface of the objects, and the temperature distributions differ from each others with different undersurface structures. Consequently, infrared radiation is useful for diagnosis of the conditions on the surface and undersurface of electric power apparatus. But the present, because engineers directly measure the temperatures of apparatuses in off-line, the measured data do not always have the information of the past. The proposed system is able to analyze not only the information of the past but the trend of deterioration, and the system is able to compensate for the distortion of surface temperature as to weather conditions. The thermal image histogram is equalized to upgrade observability, and a pan-tilter is adopted to control of direction for any target point.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.4
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• pp.255-260
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• 2018

In recent years, increasing electricity use has led to considerable interest in green energy. In order to effectively supply, cut off, and operate an electric power system, many electric power facilities such as gas insulation switch (GIS), cable, and large substation facilities with higher densities are being developed to meet demand. However, because of the increased use of aging electric power facilities, safety problems are emerging. Electromagnetic wave and leakage current detection are mainly used as sensing methods to detect live-line partial discharges. Although electromagnetic sensors are excellent at providing an initial diagnosis and very reliable, it is difficult to precisely determine the fault point, while leakage current sensors require a connection to the ground line and are very vulnerable to line noise. The partial discharge characteristic in particular is accompanied by statistical irregularity, and it has been reported that proper statistical processing of data is very important. Therefore, in this paper, we present the results of analyzing ${\Phi}-q-n$ cluster distributions of partial discharge characteristics by using K-means clustering to develop an expert partial discharge diagnosis system generated in a GIS facility.