• 조명전기설비학회논문지
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• 제23권5호
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• pp.18-28
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• 2009

고정자 권선의 단락으로 인한 고장을 해석하고 진단 알고리즘의 효과적인 시험 평가를 위해 사용될 수 있는 인버터 구동 영구자석 동기전동기의 고장모델이 제시된다. 기존에 전동기의 해석과 제어에 많이 사용되는 dq 모델은 상전압 모델을 변환한 것으로 전동기 고정자의 권선 단락 시에는 더 이상 3상평형 조건이 성립하지 않기 때문에 인버터 극전압으로부터 전동기 입력 전압을 구하기가 쉽지 않아 고장모델의 해석을 위해서 사용하기 어렵다. 이를 해결하기 위해 전동기 3상 변수와 선전압 관계식을 이용한 전동기의 고장모델이 제안된다. 제안된 고장모델의 타당성을 입증하기 위해 시뮬레이션이 수행되며 내부 고정자의 권선 단락이 가능하도록 제작된 전동기와 DSP TMS320F28335를 이용한 제어 시스템에 의해 동일 고장 조건에서 비교 실험이 수행된다.

• 대한전기학회논문지:전력기술부문A
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• 제50권5호
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• pp.211-217
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• 2001

This paper proposes a new fault detection criterion logic that extracts the features of magnetizing inrush and internal faults by making use of Daubechies Wavelet Transform which analyzes distinct features. To prove the effectiveness of proposed method, the paper constructs power system model including power transformer by using EMTP, and collects data through simulation using various fault inception angle and magnetizing inrush. The conclusions implemented by the C program and the Wavemenu of MATLAB Toolbos are more effective and simpler to distinguish inter-turn faults from magnetizing inrush states.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 춘계학술대회 논문집 초전도 자성체 연구회
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• pp.65-68
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• 2003

Interconnected power system operation has given rise to the problem of increased fault levels and leads to over stressing of all the components. Use have been made of recently developed high Tc superconductor in devising a superconducting fault current limiter (SFCL) that promises optimum performance in terms of capital cost, size, auto sensing, operational losses, response time and reliability. Recently, research about the application of the SFCL is actively progressing in Korea. To be applied for SFCL practically, the electrical insulation design of SFCL must be developed. Therefore, this paper presents the result of an investigation of the dielectric characteristics of turn-to-turn insulation for SFCL in liquid nitrogen. The dielectric characteristics of turn-to-turn insulation models of SFCL were investigated. We obtained following results. The breakdown voltages increased as the spacer thickness and length increased. And the breakdown voltages of turn-to-turn model without spacer were higher than the breakdown voltages of turn-to-turn model with spacer under impulse as well as AC voltages. The information gathered in this test series should be helpful in the design of liquid nitrogen filled SFCL.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권2호
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• pp.99-104
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• 2009

The turn-to-turn short is one major fault of the motor faults of BLDC motors and can appear frequently. When the fault happens, the motor can be operated without breakdown, but it is necessary to maintain the motor for continuous working. In past research, several methods have been applied to detect winding faults. The representative approaches have been focusing on current signals, which can give important information to extract features and to detect faults. In this study, current sensors were installed to measure signals for fault detection of BLDC motors. In this study, the Park's vector method was used to extract the features and to isolate the faults from the current measured by sensors. Because this method can consider the three-phase current values, it is useful to detect features from one-phase and three-phase faults. After extracting two-dimensional features, the final feature was generated by using the two-dimensional values using the distance equation. The values were used in fuzzy similarity to isolate the faults. Fuzzy similarity is an available tool to diagnose the fault without model generation and the fault was converted to the percentage value that can be considered as possibility of the fault.

• Journal of Power Electronics
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• 제8권2호
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• pp.181-191
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• 2008

The task performed by induction motors grows increasingly complex in modern industry and hence improvements are sought in the field of fault diagnosis. It is essential to diagnose faults at their very inception, as unscheduled machine down time can upset critical dead lines and cause heavy financial losses. Artificial intelligence (AI) techniques have proved their ability in detection of incipient faults in electrical machines. This paper presents an application of AI techniques for the detection of inter-turn insulation and bearing wear faults in single-phase induction motors. The single-phase induction motor is considered a proto type model to create inter-turn insulation and bearing wear faults. The experimental data for motor intake current, rotor speed, stator winding temperature, bearing temperature and noise of the motor under running condition was generated in the laboratory. The different types of fault detectors were developed based upon three different AI techniques. The input parameters for these detectors were varied from two to five sequentially. The comparisons were made and the best fault detector was determined.

• 전기학회논문지
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• 제58권10호
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• pp.2000-2004
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• 2009

In general, for the condition monitoring of a power transformer using the UHF PD measuring technique, detection of any partial discharge, identifying the defect in the transformer and locating the insulation defect are necessary. In this paper one of the most frequent detects which can result in turn to turn fault in power transformer was examined for identifying the defect. In order to model the defect, as a discharge source, a partial discharge cell was used for experimental activity. Magnitude of electromagnetic wave signals and corresponding amount of apparent discharge were measured simultaneously against phase of applied voltage to the discharge cell. Frequency range and phase resolved partial discharge signals were measured and analyzed. The results will be contributed to build the defect database of power transformer and to decrease the occurrence of transformer faults.

• 한국초전도저온공학회:학술대회논문집
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• 한국초전도저온공학회 2003년도 추계학술대회 논문집
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• pp.263-268
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• 2003

The Electrical insulation design and testing of high temperature superconducting (HTS) coil for high temperature superconducting fault current limiter (HTSFCL) has been performed. Electrical insulating factors of HTS coil for HTSFCL are turn-to-turn, layer-to-layer. The electrical insulation of turn-to-turn depends on surface length, and the electrical insulation of layer-to-layer depends on surface length and breakdown strength of L$N_2$. Therefore, two basic characteristics of breakdown and flashover voltage were experimentally investigated to design electrical insulation for 6.6㎸ Class HTSFCL. We used Weibull distribution to set electric field strength for insulation design. And mini-model HTS coil for HTSFCL was designed by using Weibull distribution and was manufactured to investigate breakdown characteristics. The mini-model HTS coil had passed in AC and Impulse withstand test.

• 조명전기설비학회논문지
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• 제21권5호
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• pp.60-67
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• 2007

본 논문에서는 전력계통에서 발생되는 surge나 고장전류에 의해서 변압기의 고압측 권선에 선간단락이 발생할 경우 유도되는 전자력의 크기를 유한요소 전자계해석 프로그램을 이용하여 해석하는 방법을 제안하였다. 연구에서 사용된 배전용 변압기 model은 1[MVA], 22,900/220[V] 단상 외철형 Cable 권선형 변압기로서 권선간 단락을 모의하는 방법을 제안하고, FEM 프로그램(FLUX2D)을 이용하여 단락전류와 각방향의 전자력을 계산하고 분석하였다. 누설자속분포, 권선단락 시 전압 및 전류파형, 권선간에 작용하는 힘의 변화와 분포를 계산하였다. Simulation 방법의 타당성을 검증하기 위하여 이론치와 Pspice 프로그램을 이용하여 계산한 결과와 5[%] 이내의 오차율로 아주 잘 일치함을 확인하였다. 선간단락전류는 정격전류의 약 400배이며, 전자력도 $20{\sim}200$배 정도로 급증하였다. 본 연구의 결과는 배전용 변압기의 신뢰도 향상을 위하여 변압기 코일과 절연구조 설계에 유용한 정보를 제공하게 될 것이다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.539-542
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• 2003

A motor is the workhorse of our industry. The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. Different internal motor faults (e.g., inter-turn short circuits, broken bearings, broken rotor bars) along with external motor faults (e.g., phase failure, mechanical overload, blocked rotor) are expected to happen sooner or later. This paper introduces the fault detection technique of induction motors based upon the stator current. The fault motors have rotor bar broken or rotor unbalance defect, respectively. The stator currents are measured by the current meters and stored by the time domain. The time domain is not suitable to represent the current signals, so the frequency domain is applied to display the signals. The Fourier Transformer is used for the conversion of the signal. After the conversion of the signals, the features of the signals have to be extracted by the signal processing methods like a wavelet analysis, a spectrum analysis, etc. The discovered features are entered to the pattern classification model such as a neural network model, a polynomial neural network, a fuzzy inference model, etc. This paper describes the fault detection results that use wavelet decomposition. The wavelet analysis is very useful method for the time and frequency domain each. Also it is powerful method to detect the features in the signals.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2012년도 제42회 동계 정기 학술대회 초록집
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• pp.241-241
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• 2012

Semiconductor industry has been taking the advantage of improvements in process technology in order to maintain reduced device geometries and stringent performance specifications. This results in semiconductor manufacturing processes became hundreds in sequence, it is continuously expected to be increased. This may in turn reduce the yield. With a large amount of investment at stake, this motivates tighter process control and fault diagnosis. The continuous improvement in semiconductor industry demands advancements in process control and monitoring to the same degree. Any fault in the process must be detected and classified with a high degree of precision, and it is desired to be diagnosed if possible. The detected abnormality in the system is then classified to locate the source of the variation. The performance of a fault detection system is directly reflected in the yield. Therefore a highly capable fault detection system is always desirable. In this research, time series modeling of the data from an etch equipment has been investigated for the ultimate purpose of fault diagnosis. The tool data consisted of number of different parameters each being recorded at fixed time points. As the data had been collected for a number of runs, it was not synchronized due to variable delays and offsets in data acquisition system and networks. The data was then synchronized using a variant of Dynamic Time Warping (DTW) algorithm. The AutoRegressive Integrated Moving Average (ARIMA) model was then applied on the synchronized data. The ARIMA model combines both the Autoregressive model and the Moving Average model to relate the present value of the time series to its past values. As the new values of parameters are received from the equipment, the model uses them and the previous ones to provide predictions of one step ahead for each parameter. The statistical comparison of these predictions with the actual values, gives us the each parameter's probability of fault, at each time point and (once a run gets finished) for each run. This work will be extended by applying a suitable probability generating function and combining the probabilities of different parameters using Dempster-Shafer Theory (DST). DST provides a way to combine evidence that is available from different sources and gives a joint degree of belief in a hypothesis. This will give us a combined belief of fault in the process with a high precision.