• 전기학회논문지
• /
• 제65권12호
• /
• pp.2113-2118
• /
• 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
• /
• 제15권3호
• /
• pp.520-537
• /
• 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.

• 품질경영학회지
• /
• 제51권3호
• /
• pp.435-444
• /
• 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.

• Nuclear Engineering and Technology
• /
• 제56권5호
• /
• pp.1725-1732
• /
• 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.

• 디지털산업정보학회논문지
• /
• 제13권2호
• /
• pp.1-11
• /
• 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.

• 한국수자원학회논문집
• /
• 제56권5호
• /
• pp.347-356
• /
• 2023

상수도시스템에서는 적수 및 누수와 같은 다양한 수리 및 수질적 비정상상황이 발생한다. 이를 방지하거나 빠르게 복구하기 위하여 다양한 계측기에서 얻어지는 데이터를 통해 사고를 예상하고 탐지한다. 하지만 대표적인 수리학적 비정상상황인 누수의 경우 직접적인 탐사를 수행하지 않는다면 발견되기 어렵다. 그 중 미신고 파열누수의 경우 육안식별이 어렵기 때문에 가장 많은 누수를 차지하게 되며 이는 곧 큰 경제적 손실로 이어진다. 직접적인 탐사의 경우 전문인력 확보 등 현장의 여건 등 여러 한계점이 존재한다. 이를 해결하기 위해 본 연구에서는 검보정이 완료된 상수도관망 수리모형(EPANET)의 수리해석결과 데이터를 학습데이터로 사용하고 Deep neural network 알고리즘을 활용하여 누수규모 및 누수위치에 대한 누수탐사를 수행하였다. 누수탐사 수행을 위해 모의 누수 사고데이터를 생성하였으며 누수규모, 위치 등 다양한 시나리오를 고려하였다. 또한, 최적의 누수 탐지 성능을 위해 관망의 크기, 계측기의 종류, 개수, 위치에 따른 탐지성능을 분석하였다.

• Nuclear Engineering and Technology
• /
• 제54권7호
• /
• pp.2748-2754
• /
• 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.

• 상하수도학회지
• /
• 제34권2호
• /
• pp.139-147
• /
• 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.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2011년도 춘계학술대회 논문집
• /
• pp.136-141
• /
• 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.

• 전기학회논문지P
• /
• 제58권2호
• /
• pp.221-226
• /
• 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.