• Title/Summary/Keyword: Leakage detection model

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Dynamic data validation and reconciliation for improving the detection of sodium leakage in a sodium-cooled fast reactor

  • Sangjun Park;Jongin Yang;Jewhan Lee;Gyunyoung Heo
    • 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.

Determination of a priority for leakage restoration considering the scale of damage in for water distribution systems (피해규모를 고려한 용수공급시스템 누수복구 우선순위 선정)

  • Kim, Ryul;Kwon, Hui Geun;Choi, Young Hwan
    • Journal of Korea Water Resources Association
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    • v.56 no.10
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    • pp.679-690
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    • 2023
  • Leakage is one of the representative abnormal conditions in Water distribution systems (WDSs). Leakage can potentially occur and cause immediate economic and hydraulic damage upon occurrence. Therefore, leakage detection is essential, but WDSs are located underground, it is difficult. Moreover, when multiple leakage occurs, it is required to prioritize restoration according to the scale and location of the leakage, applying for an optimal restoration framework can be advantageous in terms of system resilience. In this study, various leakage scenarios were generated based on the WDSs hydraulic model, and leakage detection was carried out containing location and scale using a Deep learning-based model. Finally, the leakage location and scale obtained from the detection results were used as a factor for the priority of leakage restoration, and the results of the priority of leakage restoration were derived. The priority of leakage restoration considered not only hydraulic factors but also socio-economic factors (e.g., leakage scale, important facilities).

Relative humidity prediction of a leakage area for small RCS leakage quantification by applying the Bi-LSTM neural networks

  • Sang Hyun Lee;Hye Seon Jo;Man Gyun Na
    • 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.

Subsurface Contaminant Leak Detection System using Electrical Resistivity Measurement (전기비저항을 이용한 지반오염누출감지시스템 개발)

  • 박준범;오명학;이주형
    • Proceedings of the Korean Geotechical Society Conference
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    • 2001.11a
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    • pp.42-71
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    • 2001
  • Leakage detection system can possibly locate leak point without laboratory analysis. Several different types of sensors provide these benefits. But the use of these technologies is not widespread, mainly because of cost. Each of the leakage detection systems available has different advantages and disadvantages. The ideal system would be affordable, durable enough to last through the life of the landfill, automated, and applicable to all types of landfills. The laboratory tests were performed to investigate the relationship between electrical resistivity and the unsaturated subsurface condition and to evaluate the contamination due to leachate based on measuring electrical resistivity. The results of experiment show that the electrical resistivity of soil decreases as moisture density increases. The electrical resistivity of soil decreases as the concentration of leachate in pore fluid increases. These facts indicate that electrical resistivity method can be a promising tool in detecting of leachate. Also, the field model tests were conducted to verify that detection of leachate leak point on detection system using electrical characteristics is accurate. Field model test results of leakage detection system imply that the leakage detection system using electrical characteristics have the great potential of detecting exactly the leak point of leachate.

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Estimation of Probability Density Functions of Damage Parameter for Valve Leakage Detection in Reciprocating Pump Used in Nuclear Power Plants

  • Lee, Jong Kyeom;Kim, Tae Yun;Kim, Hyun Su;Chai, Jang-Bom;Lee, Jin Woo
    • Nuclear Engineering and Technology
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    • v.48 no.5
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    • pp.1280-1290
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    • 2016
  • This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

A Study on the Insider Behavior Analysis Using Machine Learning for Detecting Information Leakage (정보 유출 탐지를 위한 머신 러닝 기반 내부자 행위 분석 연구)

  • Kauh, Janghyuk;Lee, Dongho
    • 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.

Leakage detection of pipeline system based on modeling and identification (모델링과 검증에 의한 파이프 라인 시스템의 유출 탐지)

  • ;;;Lee, K. S.;Song, H. K.
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.905-910
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    • 1991
  • This paper presets a leakage detection method based on modeling the leakage in pipeline systems. For gas pipeline systems, a method based on the state space model is suggested. For liquid pipeline systems, an experiment based on the static model equation was performed. In the experiment, it was possible to detect the leak and to diagnosis the leak situation within the error of .+-.3%.

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H Observer Design for Detecting Internal Oil Leakage in a Hydraulic Cylinder (유압실린더 내부 누유 검출을 위한 H 관측기 설계)

  • Jee, Sung Chul;Kang, Hyungjoo;Lee, Mun-Jik;Li, Ji-Hong
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.2
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    • pp.117-125
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    • 2016
  • This paper presents the internal oil leakage detection problem for a hydraulic double-rod cylinder. We represent the dynamics of the hydraulic cylinder as a convex combination of linear equations. To detect oil leakage, we propose a model-based fault detection observer design scheme. The observer is designed to be robust against disturbance. Sufficient design conditions are derived in the form of linear matrix inequalities. A numerical example is provided to verify the proposed techniques.

Feasibility Study on the Landfill Monitoring and Leakage Detection System

  • Park, Jun-Boum;Kwon, Ki-Bum;Oh, Myoung-Hak;Mishra, Anil Kumar
    • Proceedings of the Korean Geotechical Society Conference
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    • 2007.09a
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    • pp.558-569
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    • 2007
  • It is important to obtain real-time data from long-term monitoring of landfills and develop leachate leakage detection system for the integrated management of landfills. A novel real time monitoring system and early leakage detection system was suggested in this study. The suggested monitoring system is composed of two parts; (1) a set of moisture sensors which monitor the areas surrounding the landfill, and (2) a set of moisture and temperature sensors which monitor the landfill inside. For the assessment for landfills stabilization, real-time monitoring system was evaluated in dry and wet cell of pilot-site. In addition, the grid-net electrical conductivity measurement system was also suggested as early leakage detection system. In this study, the field applicability of suggested systems was evaluated through pilot-scale field tests. The results of pilot-scale field model tests indicate that the grid-net electrical conductivity measurement method can be applicable to the detection of landfill leachate at the initial stage of intrusion, and thus has a potential for monitoring leachate leakage at waste landfills.

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T—S Fuzzy Model-based Sampled-data Observer Design for Detecting Internal Oil Leakage in Single-rod Hydraulic Cylinder: LMI Approach (편로드 유압실린더 내부 누유 검출을 위한 T—S 퍼지 모델 기반 샘플치 관측기 설계: LMI 접근법)

  • Jee, Sung Chul;Kim, Hyogon;Park, Jeongwoo;Lee, Mun-Jik;Kang, Hyungjoo;Li, Ji-Hong
    • 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.