• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.419-424
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• 2011

The system-on-board detectable and controllable the electrical fires due to ground fault(GF), arc fault and overload is implemented. The system IC for controlling and preventing the electrical fires is available to this system. The GF detection circuit for detecting the electrical leakage current, the arc fault detection circuit and the overload detection circuit controllable the input voltage for flowing the overload current are designed. The GF detection circuit and the arc fault detection circuit are good operated to the electrical leakage current and the arc signal, respectively. It is confirmed that the overload detection circuit has shown no erratic operation with the noise or the load variation and is only operated at the overload condition.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.12
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• pp.1803-1808
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• 2013

To maintain contact between catenary and pantograph copper is important in order to transmit power smoothly on Current collection system. But, Arc discharge with strong light is generated because of contact loss. Therefore, Arc discharge detection is important measurement factor judging performance of current collection system. In this paper, It is described to results of arc discharge applying UV detection technology using arc generator. And Arc discharge was detected using the most commonly used processing catenary and rigid catenary and pantograph copper of electric rolling stock for securing arc detection instrument reliability. Results of contact loss detection instrument in this paper will be used for maintenance of current collection quality and system.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.461-462
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• 2007

DC Arc is an electric discharge which is occurred in two oppolsite electrode when system operating with DC current appliance. In this paper, DC arc detection system is designed for the display of DC arc fault current which is occurred in the local electric network with DC Power. This DC arc is one of the main causes of electric fire of dc system. Arc fault in electrical network has the characteristics of low current, high impedance and low frequency. DC Arc current detection device is designed for the display of arc fault current which has the modified arc characteristics.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.5
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• pp.520-524
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• 2023

An algorithm was developed to detect and block serial arc currents using HPF. The AC series arc problem is that the load current is greater than the fault current and no leakage current occurs. As a solution, an arc detection method utilizing differences in high- frequency amplitudes was developed. HPT was applied to the load current and FFT was applied to eliminate low frequencies. An algorithm has been developed to detect arc waveforms when they exceed a certain value compared to the average of normal waveforms. Using one cycle of data, arc detection is faster and arc accidents are prevented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.6
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• pp.995-1000
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• 2017

In this paper, we present an electrical arc detection algorithm using the mash-up analysis technique which is the core technology for the autonomous electrical safety management system(AESMS) of the multi-unit dwellings. The mash-up analysis technique analyzes the voltage, load current, zero phase current data simultaneously to judge arc faults. In order to develop the arc fault detection algorithm, the characteristics of series arc and parallel arc were analyzed. Also, we propose the mash-up analysis technique that analyzes waveforms of voltage, load current, and zero phase current at the same time. The arc fault detection algorithm was developed using the mash-up analysis technique. The developed algorithm can prevent electrical disasters in an effective way through accident prediction, and it will be used as a basic technology to introduce an autonomous electrical safety management system.

• Fire Science and Engineering
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• v.26 no.6
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• pp.24-30
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• 2012

This study is on the method of the detection for flame and series arc which can be happened at poor contact point added a vibration in part of contact point of low voltage line. In general, the causes of electric fire are over current, short circuit, poor contact, ect. The over-current or short circuit among those causes is detected by measuring a instant current value, but poor contact is difficult to detect by measuring a excessive value of the voltage and current and a distortion of waveforms. And therefore, in this paper, it is studied on the optimal technique of the arc judgement using fuzzy logic and MDET (Multi Dimension Estimation Technique). And it carries out the simulation for arc detection and the experiment for controller and load test. In result, the controller and detection algoristhm, is classified with normal wave and abnormal arc wave without relation with each loads and so the controller can detect a series arc successfully.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.566-574
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• 2021

The arc is one of factors causing electrical fires. Over past decades, various researches have been carried out to detect arc occurrences. Even though frequency analysis, wavelet and statistical features have been used, arc detection performance is degraded due to diverse arc waveforms. On the contray, Deep neural network (DNN) direcly utilizes raw data without feature extraction, based on end-to-end learning. However, a disadvantage of the DNN is processing complexity, posing the difficulty of being migrated into a termnial device. To solve this, this paper proposes an arc detection method using a logistic regression that is one of simple machine learning methods.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.3
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• pp.102-106
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• 2015

In order to avoid the electrical fire, AFCI(Arc Fault Cirruit Interrupter) has been obligated to be adopted in the United States of America since 2002. A study was carried out on how to detect Arc. In this paper, The propose is high-frequency signal detection methods and RSSI(Received Signal Strength Indication) signal processing algorithm for Arc detection. and the electrical characteristics were verifying.

• Journal of Magnetics
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• v.21 no.2
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• pp.204-208
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• 2016

This paper demonstrates the key parameter detection for smelting of submerged arc furnace (SAF) based on magnetic field radiation. A magnetic field radiation model for the inner structure of SAF is established based on relative theory of electromagnetic field. A simple equipment of 3D magnetic field detection system is developed by theoretical derivation and simulation. The experiments are carried out under the environment of industrial field and AC magnetic field generated by electrode currents and molten currents in the furnace is reflected outside of the furnace. The experimental results show that the key parameters of smelting including the position of electrode tip, the length of electric arc, and the liquid level of molten bath can be achieved. The computed tomography for SAF can be realized by the detection for smelting.

• 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.