• 전기학회논문지
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• 제60권3호
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• pp.524-530
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• 2011

This paper analyzes fault tolerance under a stator turn fault, according to the winding configuration. Improvement of torque characteristics and fault tolerance can be achieved by winding configuration without additional methods. And, torque characteristics and fault tolerance according to the winding configuration can be usually analyzed by analytical method. But, when the stator turn fault generates, compare to the steady-state, analysis of torque characteristics and fault tolerance using the analytical method is not accurate because it does not reflect influence in mutual inductance and magnetic non-linearity. Therefore, analysis of torque characteristics and fault tolerance has to be performed by using the numerical method under fault condition. This paper develops fault characteristics according to the winding configuration using the FEM-base model considered magnetic non-linearity. And, this paper suggests fault tolerance improvement according to the winding configuration, by the comparison of 8/12 and 10/12 models, under fault condition.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 추계학술대회 논문집 전기물성,응용부문
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• pp.112-116
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• 2004

On-line monitoring of fault discharge is an important approach for indicating the condition of electrical insulation of stator winding in high voltage motor. In this paper, several key aspects of on-line monitoring system are discussed, involving the characteristics of fault discharge of stator winding in high voltage motor, spectrum analysis of four simulation fault signals, feature extraction of internal fault discharge from apply voltage to breakdown. The study of the partial discharge activities allows to highlight the ageing stage in the winding fault under test. During the life of the winding insulation fault, the shape of PD signal change relating to the ageing stage. The ageing of stator winding insulation fault of high voltage motor is investigated based on the characteristics of partial discharge pulse distribution and statistical parameters, such as maximum, skewness and kurtosis using discrete wavelet transform coefficients.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2005년도 하계학술대회 논문집 Vol.6
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• pp.225-226
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• 2005

In this Study, we have acquired 5-simulation Fault types Signals of high voltage Motor stator winding using epoxy/mica coupler. In order to know stator winding fault type using fault signals, we have performed feature extraction to apply wavelet transform technique. we have obtained skewness and kurtosis as statistical parameters of fault signal pattern from non deterioration state winding. We have know that 5 fault signals types have done an exponential function pattern shape but individually fault a class widely was different each other a signal waveform of pattern.

• 전기학회논문지P
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• 제55권4호
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• pp.202-206
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• 2006

In this paper, an auto detection method of stator winding fault of small induction motor is suggested. The Park's vector pattern which is obtained from 3-phase current signal by d-q transforming, is very good to detect winding fault. Comparing the Park's vector pattern of testing motor with its of healthy motor, the Park's vector pattern of fault motor is became an ellipse and the asymmetry is increased by the winding fault series. So for detecting the dis-symmetry, id-filtered function, Min-value, and Max-value are suggested for auto detecting. Using LabVIEW programing, 3-phase healthy motor and several kind of winding fault motors are tested and the test results are shown that the suggested method can gives us a possibility of an auto detecting winding fault.

• 한국정보통신학회논문지
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• 제7권6호
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• pp.1291-1296
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• 2003

본 연구는 3상 소형 유도전동기의 고정자 권선 고장의 효과적인 진단을 위하여 고정자 전류에 대하여 Park's Vector 기법을 적용하였다. 본 기법은 고정자 3상 전류를 측정하여 Park's vector 변환을 통하여 직축, 횡축 전류로 변환하고, 이를 이용하여 고장 진단을 위한 Park's Vector Pattern을 얻어 정상 상태 패턴과 고장 권선 패턴을 비교하였다. 고정자 권선 한 상에 2턴, 10턴, 그리고 20 턴의 단락고장을 발생시켜 정격부하의 25%, 50%, 100% 부하변동에 따른 각각의 Park's Vector Pattern을 비교하여 얻은 실험 결과는 제안한 방법의 유용성을 보여준다.

• Journal of Power Electronics
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• 제13권4호
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• pp.552-557
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• 2013

This paper proposed an analytical model for the distributed magnetic field analysis of interior permanent magnet-type blush-less direct current motors under the stator-turn fault condition using the winding function theory. Stator-turn faults cause significant changes in electric and magnetic characteristic. Therefore, many studies on stator-turn faults have been performed by simulation of the finite element method because of its non-linear characteristic. However, this is difficult to apply to on-line fault detection systems because the processing time of the finite element method is very long. Fault-tolerant control systems require diagnostic methods that have simple processing systems and can produce accurate information. Thus analytical modeling of a stator-turn fault has been performed using the winding function theory, and the distributed magnetic characteristics have been analyzed under the fault condition. The proposed analytical model was verified using the finite element method.

• 전기학회논문지P
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• 제57권2호
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• pp.160-163
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• 2008

In this paper, an auto-diagnosis method of the stator winding fault for small induction motor is suggested. 3-phase stator currents are sampled, filtered, and transformed with Park's vector transformation. After then Park's vector patterns are obtained. To detect the stator winding fault automatically, a distortion ratio is newly defined and compared with the one of healthy motor, and the threshold levels of distortion ratio are suggested. The 2-turn, 4-turn, 8-turn winding fault are tested with no load, 25%, 50%, 75%, and 100% rated load. The distortion ratio of the Park's vector patterns are increased as the increase of the faulted turns, but are same as the increase of the load.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2219-2226
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• 2017

This paper deals with artificial neural network approach for automatic detection of severity level of stator winding fault in induction motor. The problem is faced through modelling and simulation of induction motor with inter coil shorting in stator winding. The sum of the absolute values of difference in the peak values of phase currents from each half cycle has been chosen as the main input to the classifier. Sample values from workspace of Simulink model, which are verified with experiment setup practically, have been imported to neural network architecture. Consideration of a single input extracted from time domain simplifies and advances the fault detection technique. The output of the feed forward back propagation neural network classifies the short circuit fault level of the stator winding.

• 정보학연구
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• 제7권4호
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• pp.61-69
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• 2004

본 논문에서는 6.6kV급 고압전동기 모델 코일을 4가지의 권선의 인공적인 결함을 갖도록 제작하였다. 운전중 모의를 위해 모델 코일에 80pF의 에폭시-마이카 커플러를 설치하였으며, TGA를 사용하여 NQN, 부분방전 크기 및 부분방전 패턴 등을 측정하였다. 웨이블렛 변환기법을 이용한 고압전동기의 고정자권선의 결함에서 발생된 부분방전신호의 파형을 통하여 여러 가지의 통계적인 파라메터를 통하여 특징을 추출하였다.

• 전기학회논문지
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• 제61권4호
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• pp.643-649
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• 2012

The diagnosis technique of stator winding faults based on Motor Current Signature Analysis(MCSA) was suggested. Park's vector pattern, the circle that is drawn by d-q transformed currents($i_d$, $i_q$), is widely used for stator winding faults detection. The current Distortion Ratio(DR), defined by the ratio of max axis and min axis of ellipse of Park's vector's pattern, was more simple and powerful method than the Park's vector pattern. In this study, a calculation method of distortion ratio of Park's vector pattern was suggested for auto diagnosis of stator winding short fault and usefulness of suggested calculation method of distortion ratio was verified through simulation using LabVIEW program.