• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.447-452
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• 2013

In this paper, the leakage current detection and auto shut-off module for a concent has been developed. Existing leakage current detection modules are detecting resistive leakage current, using a resistive leakage current detection chip but the proposed leakage current detection module separates and detects resistive leakage current in the synthesis leakage current by only programming in a power processor MCU(MSP430). The module implemented by proposed method has early detection and auto shut-off feature at more than resistive leakage current 5mA, and has the advantage of easily adjusting resistive leakage current less or more than 5mA, because of resistive leakage current detection function being implemented by a program in MCU.

• 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.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1528-1539
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• 2023

Since the leakage of sodium in an SFR (sodium-cooled fast reactor) causes an explosion upon reaction with air and water, sodium leakages represent an important safety issue. In this study, a novel technique for improving the reliability of sodium leakage detection applying DDVR (dynamic data validation and reconciliation) is proposed and verified to resolve this technical issue. DDVR is an approach that aims to improve the accuracy of a target system in a dynamic state by minimizing random errors, such as from the uncertainty of instruments and the surrounding environment, and by eliminating gross errors, such as instrument failure, miscalibration, or aging, using the spatial redundancy of measurements in a physical model and the reliability information of the instruments. DDVR also makes it possible to estimate the state of unmeasured points. To validate this approach for supporting sodium leakage detection, this study applies experimental data from a sodium leakage detection experiment performed by the Korea Atomic Energy Research Institute. The validation results show that the reliability of sodium leakage detection is improved by cooperation between DDVR and hardware measurements. Based on these findings, technology integrating software and hardware approaches is suggested to improve the reliability of sodium leakage detection by presenting the expected true state of the system.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.5
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• pp.611-619
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• 2013

In this study, Back Tracing Calculation Method was developed to determine the leakage location and leakage amount. Previously developed determination method of monitoring location and newly developed Back Tracing Calculation Method were applied to the sample pipe network and real size pilot plant. After leakage was assumed in the pilot plant, leakage location and leakage amount could be traced by Back Tracing Calculation Method. From the results, it was found that Back Tracing Calculation Method can be applied for the leakage detection in water distribution system. Furthermore, this method can be applied for the pressure management or leakage detection as a pressure control method in water distribution system.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1725-1732
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• 2024

In nuclear power plants, reactor coolant leakage can occur due to various reasons. Early detection of leaks is crucial for maintaining the safety of nuclear power plants. Currently, a detection system is being developed in Korea to identify reactor coolant system (RCS) leakage of less than 0.5 gpm. Typically, RCS leaks are detected by monitoring temperature, humidity, and radioactivity in the containment, and a water level in the sump. However, detecting small leaks proves challenging because the resulting changes in the containment humidity and temperature, and the sump water level are minimal. To address these issues and improve leak detection speed, it is necessary to quantify the leaks and develop an artificial intelligence-based leak detection system. In this study, we employed bidirectional long short-term memory, which are types of neural networks used in artificial intelligence, to predict the relative humidity in the leakage area for leak quantification. Additionally, an optimization technique was implemented to reduce learning time and enhance prediction performance. Through evaluation of the developed artificial intelligence model's prediction accuracy, we expect it to be valuable for future leak detection systems by accurately predicting the relative humidity in a leakage area.

• Journal of the Korean Society of Safety
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• v.14 no.1
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• pp.66-72
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• 1999

Local heating transportation pipe has sensor and return lines to detect water-leakage. There are impulse and resistance comparison measurement types for a water-leakage detection. The impulse type shows large detection error within a measurement range. Since the resistance comparison type can find a comparative accurate single water-leakage point in the measurement range of heating pipe, it has been used to detect water-leakages these days. However if the multi water-leakages are happened in the measurement range of transportation pipe. the resistance comparison type shows a detection error point by the parallel resistance between a detection sensor line and ground. But the detection error will be minimized by the divided transportation pipe loops. In this research, it suggests the design of remote controlled detection system which can divide a large pipe loop and a possible single water-leakage measurement process in each divided loops.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.798-804
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• 2009

Damaged liners may be detected by using leakage detection systems. For the reason, many types of leakage detection systems are applied to analyze or detect damages of lining system such as electrical detection method for the landfill sites. However, most of them can be applied in the new landfill construction sites because sensors should be installed in the bottom of liner systems. This paper shows a case study reviewing the development of a fence type leakage detection method, monitoring system and pilot plant test results, so that they can be economically and efficiently applied to actual used or in-use sites without a leakage detection system.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.48-54
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• 2013

With the development of IT convergence technology and the construction of infrastructure for water leakage detection, the detection technology of damaged pileline's location and size is being spotlighted. The exhaustion of water resource due to the leakage of water supply facilities renders it urgent to detect water leakage effectively. In this paper, we proposed the water leakage detection monitoring simulation using the power spectrum analysis. We measured the reflected wave signal by the proposed water leakage detection monitoring simulation. The rate variability is calculated form the acquired reflected wave signal. And the power spectrum analysis using the Fast Fourier Transform is evaluated the correlation between the water leakage's size and the reflected wave. Ultimately, this paper suggests empirical simulation to verify the adequacy and the validity. Accordingly, the satisfaction and the quality of services will be improved the efficient management by supporting the real-time water leakage detection.

• Journal of Korea Water Resources Association
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• v.50 no.9
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• pp.609-616
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• 2017

In this study, algorithm for the selecting the optimum monitoring location and leakage detection algorithm based on back tracing calculation method were developed and verified by the experiments in pilot plant of water distribution system. First of all, optimum monitoring locations were selected and pressure changes were measured due to artificial leakage by pressure gauges in pilot plant. Simulations of leakage detection was performed for the verification of back tracing calculation method as a leakage detection method. From the results, it was found that leakage locations and leakage amount were exactly estimated. Various leakage amount from $0.0005m^3/s$ to $0.0018m^3/s$ were reproduced and leakage location was detected by back tracing calculation method. It was verified that back tracing calculation method as a leakage detection method is effective.