• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2113-2118
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• 2016

The precise detection of electric leakage point of underground power cable is very important to reduce cost and time of maintenance and prevent electric shock accident through expedite repair of electric leakage point. This paper proposes a electric leakage point detection system underground power cable using of half-period modulated transmission waveform and earth electric potential measurement. The developed system is composed of transmitter to generate the wanted pulse waveform, receiver to measure and display earth electric potential by the transmitted pulse in electric leakage point and PC Software program to display of GPS coordinate on detection cable line. The performance of the electric leakage point detection system was tested in the constructed underground cable leakage detection test bed. The test results on signal generation voltage precision of signal transmitter, mean detection earth voltage, mean detection leakage current and electric leakage point detection error showed the developed system can be used in electric leakage point detection underground power cable.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.520-537
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• 2019

This paper proposes a system that can detect the data leakage pattern using a convolutional neural network based on defining the behaviors of leaking data. In this case, the leakage detection scenario of data leakage is composed of the patterns of occurrence of security logs by administration and related patterns between the security logs that are analyzed by association relationship analysis. This proposed system then detects whether the data is leaked through the convolutional neural network using an insider malicious behavior graph. Since each graph is drawn according to the leakage detection scenario of a data leakage, the system can identify the criminal insider along with the source of malicious behavior according to the results of the convolutional neural network. The results of the performance experiment using a virtual scenario show that even if a new malicious pattern that has not been previously defined is inputted into the data leakage detection system, it is possible to determine whether the data has been leaked. In addition, as compared with other data leakage detection systems, it can be seen that the proposed system is able to detect data leakage more flexibly.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.435-444
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• 2023

Purpose: To attain advanced performance certification, safety aspects along with functionality and performance are essential. Hence, this study suggests radiation leakage assessment methods for aviation security equipment during its performance certification. Methods: Detection technology guided the choice of radiation leakage assessment targets. We then detailed measurement and evaluation methods based on equipment type and operation mode. Equipment was categorized as container or box types for establishing measurement procedures. Results: We've developed specific radiation leakage assessment procedures for different types of aviation security equipment, crucial for ensuring airport safety. Using these procedures allows efficient evaluation of compliance with radiation leakage standards. Conclusion: The suggested radiation leakage assessment method aims to enhance aviation security and reliability. Future research will focus on identifying risks in novel aviation security equipment detection technologies and establishing safety standards.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.1-11
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• 2017

In this paper, we design and implement PADIL(Prediction And Detection of Information Leakage) system that predicts and detect information leakage behavior of insider by analyzing network traffic and applying a variety of machine learning methods. we defined the five-level information leakage model(Reconnaissance, Scanning, Access and Escalation, Exfiltration, Obfuscation) by referring to the cyber kill-chain model. In order to perform the machine learning for detecting information leakage, PADIL system extracts various features by analyzing the network traffic and extracts the behavioral features by comparing it with the personal profile information and extracts information leakage level features. We tested various machine learning methods and as a result, the DecisionTree algorithm showed excellent performance in information leakage detection and we showed that performance can be further improved by fine feature selection.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.347-356
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• 2023

In Water Distribution Systems (WDSs), can abnormal hydraulic and water quality conditions such as red-water phenomenon and leakage occur. To restore them, data is generated through various meters data to predict and detect. However, in the case of leakage if difficult to detect unless direct exploration is performed. Among them, unreported leakage, are not seen visually and account for the most considerable volumes of leakage, which leads to economic loss. Bur direct exploration is limited through on site conditions such as securing professional manpower. In this paper, leakage volumes and location were randomly generated for the WDS, which was assumed to be calibrated, and it was detected through a deep learning model. For abnormal data generation, the leakage was simulated using the emitter coefficient, and leakage detection was successfully performed through the generated abnormal data and normal data.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2748-2754
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• 2022

Because existing reactant coolant system (RCS) leakage detection mechanisms are insensitive to small leaks, a real-time, direct detection system with a detection threshold below 0.5 gpm·hr^-1 was studied. A beta-ray detection system using a silicon detector with good energy resolution for beta rays and a low gamma-ray response was proposed. The detection performance in the leakage condition was evaluated through experiments and simulations. The concentration of ¹⁶N in the coolant corresponding to a coolant leakage of 0.5 gpm was calculated using the analytic method and ORIGEN-ARP. Based on the concentration of ¹⁶N and the measurement of the silicon detector with ⁹⁰Sr/⁹⁰Y, the beta-ray count rate was estimated using MCNPX. To evaluate the effect of gamma rays inside the containment building, the signal-to-noise ratio (SNR) was calculated. To evaluate the count rate ratio, the radiation field inside the containment building was simulated using MCNPX, and response evaluation experiments were performed using beta and gamma rays on the silicon detector. The expected beta-ray count rate at 0.5 gpm leakage was 7.26 × 10⁵ counts/sec, and the signal-to-background count rate ratio exceeded 88 for a transport time of 10 s, demonstrating its suitability for operation inside a reactor containment building.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.2
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• pp.139-147
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• 2020

This paper suggests a nonlinear pressure consideration scheme through an unsteady pipe network analyzer for leakage detection with a portable pressure wave generator. In order to evaluate the performance of a proposal scheme, linear input pattern has been simulated and experiments had been carried out under both no leakage and one leakage conditions in a reservoir-pipeline-valve system. This method using portable pressure wave generator showed that a leakage can be detected from a reflection where a leakage is originated through time domain analysis. Meaningful similarity in pressure response between nonlinear input pattern and experimental results were found both no leakage and a leakage conditions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.136-141
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• 2011

In a power plant, an oil and steam leakage is generated once in a while. This is because the operating temperature and pressure of oil are very high. It is very difficult to monitor oil leakage, because oil leakage is almost invisible. Therefore a method to oil leakage detecting quickly and accurately is needs. In this paper, we proposed the method for the detecting oil leakage by using image processing and CCTV. To test the performance of this technique, experiments have been performed for simple case. Results show that the proposed technique is quite powerful in the oil leak detection.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.2
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• pp.221-226
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• 2009

In this paper, we analyzed form of flowing leakage current in electrical installation. Leakage current ($I_g$) is consisted of resistive leakage current($I_{gr}$), capacitive leakage current($I_{gc}$), and inductive leakage current($I_{gl}$). Resistive leakage current($I_{gr}$) is big occasion than capacitive leakage current($I_{gc}$) in system, Residual Current Protective Device(RCD) detects correctly leakage current. But,$I_{gc}$ is big occasion than $I_{gr}$, RCD is malfunctioned It is resistance to lead to electric fire in electrical device. We manufactured outlet that resistive leakage current detecting circuit is had. Manufactured outlet displayed performance exactly in leakage current of 5 mA Therefore, this product estimates that contribute on electric fire courtesy call.

• Journal of Ocean Engineering and Technology
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• v.30 no.5
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• pp.405-414
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• 2016

This paper presents an internal oil leakage detection problem for a hydraulic single-rod cylinder. We derive the dynamics of the hydraulic cylinder as a state space model, and then design a T—S fuzzy model-based fault detection observer. We adopt an H_∞ observer design scheme so that the observer is robust against disturbance and relatively sensitive to the leakage fault. Sufficient design conditions are derived in the form of linear matrix inequalities. A numerical example is provided to verify the proposed techniques.