• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.6
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• pp.616-624
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• 2003

The exhaustion of our water resource due to the leakage of waterworks renders it urgent to detect water leakage effectively. In the paper, the detection of water leakage makes use of a pound-penetrating radar(GPR). The region of water leakage is implemented by an acryl box filled with methanol, and then the scale-down experiments are performed by using the GPR system developed in our laboratory. The validity of GPR experiments is assured by showing that the measured data agree well with those finite-difference time-domain(FDTD) simulated results in the same situation. The feasibility of GPR system for the detection of water leakage is investigated by displaying B-scan images according to the distribution of water leakage.

• Journal of Mechanical Science and Technology
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• v.15 no.2
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• pp.232-238
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• 2001

Fast Fourier Transformation is employed to convert the head variation of a pipeline in the time domain to the amplitude of the frequency domain. Applying method of characteristics to a pipeline provides a significant frequency range for a surge introduced from the valve modulation. Inverse Fast Fourier Transformation and a Finite Impulse Response Filter can be used to remove any possible noise existing from the significant frequency range of an unsteady condition. A filtered signal shows higher potential for the inverse calculation of leakage detection than the noise-added signal does. The respective performances of Inverse Fast Fourier Transformation and a Finite Impulse Response Filter are compared in terms of leakage detection capability. Characteristics of the frequency range for multiple leakages were investigated to validate the effectiveness of the noise control method in the frequency domain.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4662-4679
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• 2015

Currently, the leakage of internal information has emerged as one of the most significant security concerns in enterprise computing environments. Especially, damage due to internal information leakage by insiders is more serious than that by outsiders because insiders have considerable knowledge of the system's identification and password (ID&P/W), the security system, and the main location of sensitive data. Therefore, many security companies are developing internal data leakage prevention techniques such as data leakage protection (DLP), digital right management (DRM), and system access control, etc. However, these techniques cannot effectively block the leakage of internal information by insiders who have a legitimate access authorization. The security system does not easily detect cases which a legitimate insider changes, deletes, and leaks data stored on the server. Therefore, we focused on the insider as the detection target to address this security weakness. In other words, we switched the detection target from objects (internal information) to subjects (insiders). We concentrated on biometrics signals change when an insider conducts abnormal behavior. When insiders attempt to leak internal information, they appear to display abnormal emotional conditions due to tension, agitation, and anxiety, etc. These conditions can be detected by the changes of biometrics signals such as pulse, temperature, and skin conductivity, etc. We carried out experiments in two ways in order to verify the effectiveness of the emotional recognition technology based on biometrics signals. We analyzed the possibility of internal information leakage detection using an emotional recognition technology based on biometrics signals through experiments.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.6
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• pp.605-610
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• 2016

The ELCB(: Earth Leakage Circuit Breaker) is the only way being used to prevent accidents from happening caused by electrical disaster. However, the existing ELCB has a limit to prevent damages to life and property due to a electric fire and a human body electric shock caused by the resistive leakage current, because of detecting the total leakage current in the block range of 15mA~30mA. It also has problems such as reduced productivity and reliability due to malfunctions by capacitive leakage currents. In this study, we have implemented the algorithm for the resistive leakage current detection technique and developed the resistive leakage current detection module based on a MSP430 processor, 16bit signal processor and this module can be operated in a desired block threshold within 0.03 seconds as specified in KS C 4613.

• 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.

• 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%.