• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.774-775
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• 2011

Recently, by increasing of devices which are sensitive to power quality, microprocessor and power electronics, the deterioration of power quality is accelerated. Accordingly, various methods for analysis, detection, compensation and countermeasure on power quality are proposed. For this, the study of distinction of various disturbances and fault which is occurred in power system is necessary to prior. Therefore, in this paper, the classification algorithm among steady state and single line to ground fault which is commonly occurred fault is proposed using S-Transform.

• Journal of Ocean Engineering and Technology
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• v.16 no.5
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• pp.61-65
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• 2002

The fault detection and diagnosis of rotating machinery widely used in plants including the ship are important for maintaining the performance of Plants. Recently, the wavelet transform has been recognized an efficient method to detect a little variation of physical quantities by the synchronous localization of time and frequency domains using the translation and dilation of signals. In this Paper, In order to develop efficient and reliable fault detection and diagnosis system rotating machines, the performance of wavelet transformation to detect a little variation of machine status and neural network to diagnose the cause of machine faults are investigated and experimented.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1373-1375
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• 1999

High impedance fault (HIF) is defined as fault the general overcurrent relay can not detect or interrupt. Especially when HIF occur in residential areas, energized high voltage conductor results in fire hazard, equiment damage or personal threat. This paper proposes the model of HIF in transmission line using the ZnO arrester and resistance to be implemented within EMTP. Wavelet transform is efficient and useful for the detection of HIF in power system, because it uses variable windows according to frequency. HIF detection method using wavelet transform can distinguish HIF from similar phenomena like arcfurance load, capacitor bank switching and line switching.

• Proceedings of the KIEE Conference
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• summer
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• pp.557-559
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• 2004

The study of applying wavelet transform in power cable system fault location has been recognized by many researchers and investigated. For performance of fault location, the fault generated transients can be captured at one end of the cable or both ends. Between two approaches, single-ended approach is less expensive and more reliable as it doesn't need communication link between the ends of the cable. So, we performs the approach based on the one. In this paper, we are going to introduce a new algorithm to discriminate the transient and the reflected signal using wavelet coefficient. For wavelet transform, the stationary wavelet transform(SWT) is applied instead of conventional DWT because SWT has redundancy properties which is more useful in noisy signal processing.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1097-1109
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• 2016

Fault detection and isolation are related to system monitoring, identifying when a fault has occurred, and determining the type of fault and its location. Fault detection is utilized to determine whether a problem has occurred within a certain channel or area of operation. Fault detection and diagnosis have become increasingly important for many technical processes in the development of safe and efficient advanced systems for supervision. This paper presents an integrated technique for fault diagnosis and classification for open- and short-circuit faults in three-phase inverter circuits. Discrete wavelet transform and principal component analysis are utilized to detect the discontinuity in currents caused by a fault. The features of fault diagnosis are then extracted. A fault dictionary is used to acquire details about transistor faults and the corresponding fault identification. Fault classification is performed with a fuzzy logic system and relevance vector machine (RVM). The proposed model is incorporated with a set of optimization techniques, namely, evolutionary particle swarm optimization (EPSO) and cuckoo search optimization (CSO), to improve fault detection. The combination of optimization techniques with classification techniques is analyzed. Experimental results confirm that the combination of CSO with RVM yields better results than the combinations of CSO with fuzzy logic system, EPSO with RVM, and EPSO with fuzzy logic system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.895-902
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• 2007

Rotating machinery has two typical faults with clearance, one is partial rub and the other is looseness. Due to these faults, non-linear and non-stationary signals are occurred. Therefore, time-frequency analysis is necessary for exact fault diagnosis of rotating machinery. In this paper newly developed time-frequency analysis method, HHT(Hilbert-Huang Transform) is applied to fault diagnosis and compared with other method of FFT, SFFT and CWT. The results show that HHT can represent better resolution than any other method. Consequently, the faults of rotating machinery are diagnosed efficiently by using HHT.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.522-523
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• 2014

Analysis of faults in induction motors has become a major field of research due to importance of loss and damage reduction and maximum online performance of motors. There are several methods to analyze the faults in an induction motor from conventional Fourier transform to modern decision-making neural networks. Considering detectability of fault among all methods, a new fault detection solution has been proposed; it is called as frequency-domain Discrete Wavelet Transform (FD-DWT). In this method, the stator current is decomposed through series of low- and high-pass filters and consequently, the fault characteristics are more visible, because additional components have been reduced. The objective of this paper is early detection of input voltage unbalance in induction motor using wavelet transform in frequency domain. Experimental results show the effectiveness of the proposed method in early detection of faults.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.362-368
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• 2009

Electrical fires have been occurred continuously in spite of installing ELB. Therefore the concern with the electrical arc-fault that cause the fire has growing. This paper measured series arc fault currents by the method of arc generator test in UL standard 1699. The used analysis methods in this paper are three different ways using DWT(discrete wavelet transform) those are frequently used for the arc fault current signal analysis. The arc fault detection probability is 100 % by method using noise-energy/shoulder-duration ratio of approximation coefficient. As these results, the variation of noise-energy and shoulder-duration ratio of approximation coefficient are founded important factors for the analysis of arc fault.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1191-1198
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• 2007

In this paper, the fault detection and noise cancellation algorithm based on wavelet transform was developed to locate the fault more accurately. Specially, noise cancellation algorithm was based on the correlation of wavelet coefficients at multi-scales. Fault detection, classification and location algorithm were tested by EMTP simulation on real power cable system. From these results, the faults can be detected and located even in very difficult situations, such as at different inception angle and fault resistance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1319-1322
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• 2004

In this paper, a fault diagnosis system for ram in PHWR plant is developed. The developed diagnosis system can detect the ram stuck phenomena due to increased ball wear and damage in ball nut using discrete wavelet transform before the ram is stuck. The validity of developed diagnosis system is shown via experiments using ball nut characteristic test equipment.