• 대한전기학회논문지
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• 제41권9호
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• pp.973-983
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• 1992

A very fast algorithm, using fast Haar transformation with half a cycle dc-offset free data, to extract the power frequency components and to detect faults in power systems is proposed. For the speed-up, two important techniques are used. First, according to the symmetric characteristics of sine and cosine functions, fundamental frequency components are calculated with only half a cycle sample data. For using these characteristics, post-fault de-offset components must be removed beforehand. Therefore, secondly, a newly designed digital filter is used to remove exponentially decaying dc-offset from the post-fault signal. In accordance with series simulations, transmission line faults can be detected in around half a cycle after faults.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1558-1565
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• 2015

In this paper, we propose a new method for detecting bearing faults using vibration signals. The proposed method is based on support vector machines (SVMs), which treat the harmonics of fault-related frequencies from vibration signals as fault indices. Using SVMs, the cross-validations are used for a training process, and a two-stage classification process is used for detecting bearing faults and their status. The proposed approach is applied to outer-race bearing fault detection in three-phase squirrel-cage induction motors. The experimental results show that the proposed method can effectively identify the bearing faults and their status, hence improving the accuracy of fault diagnosis.

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.2058-2064
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• 2014

In transformer fault diagnosis, dissolved gas analysis (DGA) is been widely employed for a long period and numerous methods have been innovated to interpret its results. Still in some cases it fails to identify the corresponding faults. Due to the limitation of training data and non-linearity, the estimation of key-gas ratio in the transformer oil becomes more complicated. This paper presents Intuitionistic Fuzzy expert System (IFS) to diagnose several faults in a transformer. This revised approach is well suitable to diagnosis the transformer faults and the corresponding action to be taken. The proposed method is applied to an independent data of different power transformers and various case studies of historic trends of transformer units. It has been proved to be a very advantageous tool for transformer diagnosis and upkeep planning. This method has been successfully used to identify the type of fault developing within a transformer even if there is conflict in the results of AI technique applied to DGA data.

• 대한전기학회논문지
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• 제36권9호
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• pp.678-684
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• 1987

The identification problem of instrument faults in PWR pressurizer is considered. The instrument failure detection technique in this paper consists of two filters, a normal-mode Kalman filter which estimates plant states in normal operation and a bias estimator which estimates the magnitudes and directions of bias faults. The concept of threshold based on the residual of a Kalman filter in normal operation is introduced. The bias estimator is driven when the absolute value of residual exceeds the threshold. The suggested failure detection algorithm is applied to a PWR pressurizer. Computer simulations show that the prompt detection of bias fault can be performed very successfully when there exist instrument faults.

• 대한전기학회논문지:전력기술부문A
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• 제48권6호
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• pp.665-670
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• 1999

This paper introduces a fuzzy expert systems for fault diagnosis, where the causal relationships between faults and protective devices are defined as fuzzy relations. The uncertainties existing in the fault diagnosis are figured out using the possibility theory and the possibility measure is associated with the fuzzy relation to evaluate the possibilities of faults. Besides, the knowledge base in the expert system is described and explained. In this way, multiple-fault can be handled easily and simultaneously together with single faults.

• International Journal of Control, Automation, and Systems
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• 제5권2호
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• pp.155-160
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• 2007

A fault detection and isolation (FDI) problem is considered for inertial sensors, such as gyroscopes and accelerometers and a new FDI method for double faults is proposed using reduced-order parity vector. The reduced-order parity vector (RPV) algorithm enables us to isolate double faults with 7 sensors. Averaged parity vector is used to reduce false alarm and wrong isolation, and to improve correct isolation. The RPV algorithm is analyzed by Monte-Carlo simulation and the performance is given through fault detection probability, correct isolation probability, and wrong isolation probability.

• 한국군사과학기술학회지
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• 제12권5호
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• pp.667-675
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• 2009

Faults can be generated at electric power systems by variety of both certain and uncertain reasons, which may cause harmful effects on electrical apparatuses under operation and stability of electric power system operations, and may also lead to great confusions and inconveniences to individual livings, public works, industrial activities, services, military affairs, etc.. In some cases, intentional inductions of faults are committed for specific purposes, and it is necessary to understand the procedures of fault by some foreign materials. In this paper, compositions and operations of electric power systems, summaries of electrical fault phenomena and fault protection, and restrictions to power system operation were outlined. And the analogies on the procedure of faults from former papers were introduced, and test results that revealed the validity of those analogies were also introduced.

• Journal of Electrical Engineering and Technology
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• 제9권1호
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• pp.37-44
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• 2014

This paper proposes a new diagnosis algorithm to detect broken rotor bars (BRBs) faults in induction motors. The proposed algorithm is composed of a frequency signal dimension order (FSDO) estimator and a fault decision module. The FSDO estimator finds a number of fault-related frequencies in the stator current signature. In the fault decision module, the fault diagnostic index from the FSDO estimator is used depending on the load conditions of the induction motors. Experimental results obtained in a 75 kW three-phase squirrel-cage induction motor show that the proposed diagnosis algorithm is capable of detecting BRB faults with an accuracy that is superior to a zoom multiple signal classification (ZMUSIC) and a zoom estimation of signal parameters via rotational invariance techniques (ZESPRIT).

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제54권5호
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• pp.231-237
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• 2005

Many conventional multi-level inverters have detected switching faults by using the over voltage and current. However, fault detection of the switching elements is very difficult because the voltage and current due to each switching fault decrease more than the normal operation. Moreover, the dc-link unbalancing voltage causes a serious problem in the safety and reliability of system when the 3-level inverter faults occur Therefore, this paper proposes the simple fault diagnose method and the neutral-point-voltage control method that can protect the 3-level inverter system from the unbalancing voltage of the do-link capacitors when the faults of switching elements occur in the 3-level inverter that is very efficient in ac motor drives of the high voltage and high power applications. Through experiment results, the validity of the proposed method is demonstrated.

• 조명전기설비학회논문지
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• 제28권4호
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• pp.36-41
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• 2014

Most faults that occur on transmission lines are caused by extreme weather with lightning storms in the distance. These are not only prolongs the time of removing and recovering, but also increases economical damages. If faults can be precisely located, maintenance crews can reach them quickly, and remove the faults in time. So, the precise locating of the faulted point on a transmission line is very important to improve the system reliability, and decreases economic damages as an inherent consequence of long term outages. Also, fault location methods are becoming of much importance for utilities and research. In this paper, two single-terminal impedance-based fault location techniques will be investigated to show the reliability and evaluated the performance of reactance and Takagi method by using MATHCAD program simulations.