• Proceedings of the KSR Conference
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• 2000.11a
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• pp.733-739
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• 2000

This paper is described the development of on-line partial discharge detector for high voltage apparatus. This detector consists of acoustic and high frequency current sensors, amplifier part, A/D converter part, data communication part and computer. The contents of paper are characteristics of units and digital signal processing for reducing noise in partial discharge detection. We seek methods to do good digital signal processing for detection of partial discharge. We apply digital filtering methods to the elect Tic signal and a cross con-elation to the acoustic signal. This paper shows the characteristics of these filtering method and cross con-elation in partial discharge detection.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.98-100
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• 2007

DC Arc Fault Current is an electric discharge which is occurred in two opposite electrode. In this paper, DC arc detection device 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. 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.

• The Journal of the Acoustical Society of Korea
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• v.33 no.2
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• pp.139-145
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• 2014

In this paper, a feature parameter is obtained by applying the Teager energy to the WPD(Wavelet Packet Decomposition) coefficients. The threshold value is obtained based on means and standard deviations of nonspeech frames. Experimental results by using TIMIT speech and NOISEX-92 noise databases show that the proposed algorithm is superior to the typical VAD algorithm. The ROC(Receiver Operating Characteristics) curves are used to compare performance of VAD's for SNR values of ranging from 10 to -10 dB.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.6
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• pp.16-21
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• 2005

The cutting characteristics of hardened steel(AISI 52100) by PCBN tools is investigated with respect to cutting force, workpiece surface roughness and tool flank wear by the vision system. Hard Owning is carried out with various cutting conditions; spindle rotational speed, depth of cut and feed rate. Backpropagation neural networks(BPNs) are used for detection of tool wear. The input vectors of neural network comprise of spindle rotational speed, feed rates, vision flank wear, and thrust force signals. The output is the tool wear state which is either usable or failure. The detection of the abnormal states using BPNs achieves $96.8\%$ reliability even when the spindle rotational speed and feedrate are changed.

• 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 Korea Society of Computer and Information
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• v.13 no.5
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• pp.19-26
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• 2008

In this paper, we converted an RGB into an YCbCr image input from CCD camera and then after compute difference two consecutive images, conduct Glassfire Labeling. We extract an image become ware of motion-change, if the difference between most broad(area) and Area critical value more than critical value. We enforce the detection of facial characteristics to an extracted motion-change images by using AdaBoost algorithm to extract an characteristics.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.2
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• pp.25-34
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• 2020

As leakage in nuclear power plants could cause a variety of problems, it is very critical to monitor leakage from the safety point of view. Accordingly, a new type of leak detection system is currently being developed and flow characteristics of the sampling and transportation system are investigated by using numerical analysis as a part of the development process in this study. The results showed that the steam mass fraction varied according to the effect of the gap between the insulation and piping component, transportation velocity, and material properties of porous media during the sampling and transportation process. The results of this study should be useful for understanding flow characteristics of the sampling and transportation system and its design and application.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.1-10
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• 2019

In recent years, information collection of attacks through stealth port scanning technology has become more sophisticated. The most commonly used Nmap port scanner supports a variety of stealth scanning technologies along with the existing scanning techniques. Nmap also supports Idle scan that is different from conventional stealth scans. This is a more sophisticated stealth scan technique by applying the SYN scan and ACK scan techniques. In previous studies, the detection of Idle scanning was on zombie system, but was not on victim system. In this paper, we propose an effective detection method of Idle scan on victim system. The Idle scanning is composed of two stages; they are probing the zombie and victim system and scanning the victim system. We analyzed the characteristics of the two stages. The characteristics, we captured, are that SYN and RST packets are different from normal packet. We applied them to detection method, then Idle scanning is detected effectively.

• Current Optics and Photonics
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• v.8 no.3
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• pp.239-245
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• 2024

This paper proposes single logarithmic amplification (single-LA) and deep learning (DL)-based fixed-threshold on-off keying (OOK) detection for free-space optical (FSO) communication. Multilevel LAs (MLAs) can be used to mitigate intensity fluctuations in the received OOK signal by their nonlinear gain characteristics; however, it is ineffective in the case of high scintillation, owing to degradation of the OOK signal's extinction ratio. Therefore, a DL technique is applied to realize effective scintillation compensation in single-LA applications. Fully connected (FC) networks and fully connected neural networks (FCNN), which have nonlinear modeling characteristics, are deployed in this work. The performance of the proposed method is evaluated through simulations under various scintillation effects. Simulation results show that the proposed method outperforms the conventional adaptive-threshold-decision, single-LA-based, MLA-based, FC-based, and FCNN-based OOK detection techniques.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.6
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• pp.50-55
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• 2003

This study proposed the analysis of damage detection due to the change of the stiffness of structure by using the original and modified dynamic characteristics. The present approach allows the use of composite data which consist of eigenvalues and eigenvectors. The suggested method is applied to examples of a cantilever and 3 degree of freedom system by modifying the stiffness. The predicted damage detections are in good agreement with these from the structural reanalysis using the modified stiffness.