• 한국전기전자재료학회논문지
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• 제36권6호
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• pp.614-619
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• 2023

The fault current limiting characteristics of three-phase transformer type superconducting fault current limiter (SFCL), which consisted of three-phase primary and secondary windings wound on E-I iron core, one high-TC superconducting (HTSC) element connected with the secondary winding of one phase and another HTSC element connected in parallel with other two secondary windings of two phases, were analyzed. Unlike other three-phase transformer type SFCLs with three HTSC elements, three-phase transformer type SFCL using double quench has the merit to perform fault current limiting operation for three-phase ground faults with two HTSC elements. To verify its proper three-phase ground fault current limiting operation, three-phase ground faults such as single-line ground, double-line ground and triple-line ground faults were generated in three-phase simulated power system installed with three-phase transformer type SFCL using double quench. From analysis of its fault current limiting characteristics based on tested results, three-phase transformer type SFCL using double quench was shown to be effectively operated for all three-phase ground faults.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권4호
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• pp.238-245
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• 2016

Inverters are considered the basic building blocks of industrial electrical drive systems that are widely used for various applications; however, the failure of electronic switches mainly affects the constancy of these inverters. For safe and reliable operation of an electrical drive system, faults in power electronic switches must be detected by an efficient system that is capable of identifying the type of faults. In this paper, an open switch fault identification technique for a three-phase inverter is presented. Single, double, and triple switching faults can be diagnosed using this method. The detection mechanism is based on stator current analysis. Discrete wavelet transform (DWT) using Daubechies is performed on the Clarke transformed (-) stator current and features are extracted from the wavelets. An artificial neural network is then used for the detection and identification of faults. To prove the feasibility of this method, a Simulink model of the DWT-based feature extraction scheme using a neural network for the proposed fault detection system in a three-phase inverter with an induction motor is briefly discussed with simulation results. The simulation results show that the designed system can detect faults quite efficiently, with the ability to differentiate between single and multiple switching faults.

• Journal of Power Electronics
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• 제17권4호
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• pp.972-982
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• 2017

The Park's vector of stator current is a popular technique for the detection of induction motor faults. While the detection of the faulty condition using the Park's vector technique is easy, the classification of different types of faults is intricate. This problem is overcome by the Multiple Park's Vector (MPV) approach proposed in this paper. In this technique, the characteristic fault frequency component (CFFC) of stator winding faults, rotor winding faults, unbalanced voltage and bearing faults are extracted from three phase stator currents. Due to constructional asymmetry, under the healthy condition these characteristic fault frequency components are unbalanced. In order to balanced them, a correction factor is added to the characteristic fault frequency components of three phase stator currents. Therefore, the Park's vector pattern under the healthy condition is circular in shape. This pattern is considered as a reference pattern under the healthy condition. According to the fault condition, the amplitude and phase of characteristic faults frequency components changes. Thus, the pattern of the Park's vector changes. By monitoring the variation in multiple Park's vector patterns, the type of fault and its severity level is identified. In the proposed technique, the diagnosis of faults is immune to the effects of unbalanced voltage and multiple faults. This technique is verified on a 7.5 hp three phase wound rotor induction motor (WRIM). The experimental analysis is verified by simulation results.

• 조명전기설비학회논문지
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• 제16권1호
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• pp.76-84
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• 2002

송전선과 배전선의 고장에 의한 voltage sag는 산업 수용가와 전력회사에 당면한 가장 중요한 전력품질(power quality) 문제들 중 하나가 되었다. voltage sag는 일반적으로 진폭과 지속시간 특성으로 기술되지만 voltage sag 현상을 규명하여 그 대책을 찾는데는 위상변위 특성을 반드시 고려해야 한다. 이 논문에서는 3상지락, 단선지락, 및 선간단락 사고가 발생하였을 경우에, 고장임피던스의 변화에 의한 voltage sag를 symmetrical components 해석을 이용하여 특성해석을 하였다. 이 때, voltage sag와 이들이 진폭과 위상에 미치는 효과를 고찰하였다. 3상지락과 같은 평형 고장은 모든 상에서 전압과 전류가 동일한 값으로 변화되고 또한 영상성분들은 영이 되었다. 그렇지만, 단선지락과 선간단락 고장과 같은 불평형 고장으로 인한 voltage sag는 진폭과 위상이 각 상마다 다르게 변화되었다. 해석결과를 확인하기 위하여 전력회로 모델들을 토대로 시뮬레이션을 수행하고 그 결과들도 검토되었다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.2317-2322
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• 2011

In three-phase power, when the power is supplied to the single phase load, there is the unbalance of load in the three-phase power. So the scott transformer is used in the power system to supply a single phase load in three-phase power without the unbalance of loads. Especially, the scott transformer is used in the AC substation of electric railroad. Two single phase transformers are combined by T-wiring in the scott transformer. So, two single phase voltage is provided by differing $90^{\circ}$ phase in three-phase power. The selection of related equipment and correction of protective relay are not easy from characteristic of the scott transformer when shunt and ground faults occur. In this paper, electric model of the scott transformer is suggested and the current of the scott transformer in shunt and ground faults is analyzed. Also, the scott transformer model is demonstrated by using Sinulink.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.1892-1897
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• 2010

In three-phase power, when the power is supplied to the single phase load, there is the unbalance of load in the three-phase power. So the scott transformer is used in the power system to supply a single phase load in three-phase power without the unbalance of loads. Especially, the scott transformer is used in the AC substation of electric railroad. Two single phase transformers are combined by T-wiring in the scott transformer. So, two single phase voltage is provided by differing $90^{\circ}$ phase in three-phase power. The selection of related equipment and correction of protective relay are not easy from characteristic of the scott transformer when shunt and ground faults occur. PSIM(Power Electronics Simulator) is optimal simulation software in field of the power electronics and provide the simple and convenient user interface. In this paper, electric model of the scott transformer is suggested and the current of the scott transformer in shunt and ground faults is analyzed. Also, the scott transformer model is demonstrated by using PSIM.

• 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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• 제15권1호
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• pp.288-297
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• 2015

This paper presents a novel approach to diagnose interturn insulation faults in three-phase transformers that operate at different loading conditions. This approach is based on the loci of instantaneous symmetrical components and requires the measurement of three input primary winding currents and voltages to diagnose faults in the transformer. The effect of unbalance supply conditions, load variations, constructional imbalance, and measurement errors when this methodology is used is also investigated. Wing size or length determines the loading on the transformer. Wing travel and area determine the degree of severity of fault. Experimental results are presented for a 400/200 V, 7.5 kVA transformer to validate this method.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.147-152
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• 2023

Mostly in motor fault detection the instantaneous values 3 axis vibration and 3phase current in time domain are acquired and converted to frequency domain. Vibrations are more useful in diagnosing the mechanical faults and motor current has remained more useful in electrical fault diagnosis. With having some experience and knowledge on the behavior of acquired data the electrical and mechanical faults are diagnosed through signal processing techniques or combine machine learning and signal processing techniques. In this paper, a single-layer LSTM based condition monitoring system is proposed in which the instantaneous values of three phased motor current are firstly acquired in simulated motor in in health and supply imbalance conditions in each of three stator currents. The acquired three phase current in time domain is then used to train a LSTM network, which can identify the type of fault in electrical supply of motor and phase in which the fault has occurred. Experimental results shows that the proposed single layer LSTM algorithm can identify the electrical supply faults and phase of fault with an average accuracy of 88% based on the three phase stator current as raw data without any processing or feature extraction.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권3호
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• pp.173-180
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• 2016

Fault detection and diagnosis is a task to monitor the occurrence of faults and pinpoint the exact location of faults in the system. Fault detection and diagnosis is gaining importance in development of efficient, advanced and safe industrial systems. Three phase inverter is one of the most common and excessively used power electronic system in industries. A fault diagnosis system is essential for safe and efficient usage of these inverters. This paper presents a fault detection technique and fault classification algorithm. A new feature extraction approach is proposed by using three-phase load current in three-dimensional space and neural network is used to diagnose the fault. Neural network is responsible of pinpointing the fault location. Proposed method and experiment results are presented in detail.