• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.178-184
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• 2009

An efficient fault diagnosis system is needed for industry because it can optimize the resources management and improve the performance of the system. In this study, a fault diagnostic system is proposed for rotating machine using wavelet packet transform (WPT) and elman neural network (ENN) techniques. In most fault diagnosis for mechanical systems, WPT is a well-known signal processing technique for fault detection and identification. In previous work, WPT can improve the continuous wavelet transform (CWT) used over a longer computing time and huge operand. It can also solve the frequency-band disagreement by discrete wavelet transform (DWT) only breaking up the approximation version. In the experimental work, the extracted features from the WPT are used as inputs in an Elman neural network. The results show that the scheme can reliably diagnose four different conditions and can be considered as an improvement of previous works in this field.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.494-500
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• 2008

This paper presents the analyzed result of the series arc fault current by using the discrete wavelet transform. The series arcing is caused by a loose connection in series with the load circuit. The series arc current is limited to a moderate value by the resistance of the device connected to the circuit, such as an appliance or a lighting system. The amount of energy in the sparks from the series arcing is less than in the case of parallel arcing but only a few amps are enough to be a fire hazard. Therefore, it is hard to detect the distinctive difference between a normal current and a intermittent arc current. This paper, presents the variation of the ratio of peak values and RMS values of the series arc fault current, and proposes the novel series arc fault detecting method by using the discrete wavelet transform. Loads such as a CFL lamp, a vacuum cleaner, a personal computer, and a television, which has the very similar normal current with the arc current, were selected to confirm the novel method.

• Journal of Industrial Technology
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• v.21 no.A
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• pp.105-110
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• 2001

A continuous and reliable electrical energy supply is the objective of any power system operation. A transmission line is the part of the power system where faults are most likely to happen. This paler describes the use of wavelet transform for analyzing power system fault transients in order to determine the fault location. Synchronized sampling was made possible by precise time receivers based on GPS time reference, and the sampled data were analyzed using wavelet transform. This paper describes a fault location monitoring system and fault locating algorithm with GPS, DSP processor, and data acquisition board, and presents some experimental results and error analysis.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.1
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• pp.32-37
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• 2021

This study proposes a DC series arc fault detector using a frequency analysis method called the discrete wavelet transform (DWT), in which the processing speed of the DWT algorithm is improved effectively. The processing time can be shortened because of the time characteristic of the DWT result. The performance of the developed DC series arc fault detector for a large photovoltaic system is verified with various DC series arc generation conditions. Successful DC series arc detection and improved calculation time were both demonstrated through the measured actual arc experimental result.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.11
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• pp.905-910
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• 2008

Vibration analysis is widely used in machinery diagnosis and the wavelet transform has also been implemented in many applications in the condition monitoring of machinery. In contrast to previous applications, this paper examines whether acoustic signal can be used effectively along vibration signal to detect the various local fault, in local fault of gearboxes using the wavelet transform. Moreover, envelop analysis is well known as useful tool for the detection of rolling element bearing fault. In this paper, a acoustic emission (AE) sensor is employed to detect gearbox damage by installing them around bearing housing at driven-end side. Signal processing is conducted by wavelet transform and enveloping to detect her fault all at once gearbox using AE signal.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1183-1190
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• 2007

This paper proposes the improved fault decision algorithm using DWT(Discrete Wavelet Transform) and ANNs for the FRTU(Feeder Remote Terminal Unit) on the feeder in the power distribution system. Generally, the FRTU has the fault decision scheme detecting the phase fault, the ground fault. Especially FRTU has the function for 2000ms. This function doesn't operate FI(Fault Indicator) for the Inrush current generated in switching time. But it has a defect making it impossible for the FI to be operated from the real fault current in inrush restraint time. In such a case, we can not find the fault zone from FI information. Accordingly, the improved fault recognition algorithm is needed to solve this problem. The DWT analysis gives the frequency and time-scale information. The neural network system as a fault recognition was trained to distinguish the inrush current from the fault status by a gradient descent method. In this paper, fault recognition algorithm is improved by using voltage monitoring system, DWT and neural network. All of the data were measured in actual 22.9kV power distribution system.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1130-1132
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• 1999

This paper presents the feature extraction of fault current related to the multi-shot reclosing scheme in the power distribution system. Fourier transform is used to extract the feature of the fault current waveform in the case of the temporary fault and the permanent fault. After the waveform is analyzed using Fourier transform, the magnitude spectrum and the relative variation of THD are calculated. These results are that the relative variation of THD is great in the temporary fault and is little in the permanent fault.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1470-1477
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• 2008

In this paper, a new detection method of series arc-fault signals occurring at the wiring of home appliances is proposed. The discrete wavelet transform was used for the numerical analysis of the variation rate in peak, RMS, noise energy, shoulder of the arc-fault current wave. As a results, the arc distinction threshold value of these variation rates was about 0.1 in most cases. The arc-fault current of the loads with the active PFC circuit showed a high rate of variation in noise energy and shoulder, but arc-fault current of the loads without the active PFC circuit showed a high rate of variation in peak and RMS. The arc fault current in resistive loads showed a high rate of variation in shoulder.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1855-1860
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• 2009

This paper caused a distribution utility to generation of analysis fault several cases on the ground of substation in a energy meter three phase current, voltage data measurement to fault type and characteristics. Mother wavelet transformation of suitable to method algorithm from the distribution utility to generation of fault in image impedance etc several parameter for utility characteristics effective to probatory fault point extraction.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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• pp.834-840
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• 2007

A generator plays an important role in transferring an electric power to power system networks. The generator protection systems in Korea have been imported and operated through a tum-key from overseas entirely. Therefore, a study of the generator protection field has in urgent need for a stable operation of the imported goods, and for preparation of next generation protection system. The paper describes the fault detection algorithm using WT(Wave!et Transform) of currents for a generator protection. The fault current signals after executing a terminal fault modeling collect using a MA TLAB package, and calculate the wavelet coefficients through the process of a multi -level decomposition (MLD). The proposed algorithm for a fault detection using the Daubechies WT (wavelet transform) was executed with a C language for the command line function and for the real time realization after analyzing MATLAB's graphical interface. The advanced technique had complemented the defects of a DFT by applying a Daubechies WT. and had improved faster a speed and more accurate of fault discriminant than a conventional DFR.