• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1231-1240
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• 2020

Water pipes are laid on the ground, making it impossible to visually detect leaks due to aging of pipes, and technology to detect leaks in pipes is mainly used to detect leaks in pipes by detecting leaks. In this paper, two accelerometers were attached to both ends of the constant water piping to calculate the time difference between the acquired data to detect leakage points. The leak test of piping was performed by installing valves at 4.3m, 8.6m, and 12.9m points on piping 17.2m, and changing the development rate of valves to 30% and 70%. Leakage can be detected for pressure drop in piping, which is 30% and 70% open valve. It is very important to detect leakage in the early stage, and it is judged that detection of the initial leak point from the algorithm applied in this paper will be possible.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.160-160
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• 2019

Water is a limited source that needs to be properly managed and distributed to the ever-growing population of the world. Rapid urbanization and development have increased the overall water demand of the world drastically. However, there is loss of billions of liters of water every year due to leakages in water distribution systems. Such water loss means significant financial loss for the utilities as well. World bank estimates a loss of $14 billion annually from wasted water. To address these issues and for the development of efficient and reliable leakage management techniques, high efforts have been made by the researchers and engineers. Over the past decade, various techniques and technologies have been developed for leakage management and leak detection. These include ideas such as pressure management in water distribution networks, use of Advanced Metering Infrastructure, use of machine learning algorithms, etc. For leakage detection, techniques such as acoustic technique, and in recent yeats transient test-based techniques have become popular. Smart Water Grid uses two-way real time network monitoring by utilizing sensors and devices in the water distribution system. Hence, valuable real time data of the water distribution network can be collected. Best results and outcomes may be produced by proper utilization of the collected data in unison with advanced detection and management techniques. Long term reduction in Non Revenue Water can be achieved by detecting, localizing and repairing leakages as quickly and as efficiently as possible. However, there are still numerous challenges to be met and future research works to be conducted in this field.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.10
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• pp.469-475
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• 2003

Resistive leakage current flowing ZnO blocks increases with its ages, which is an important indicator of arrester deterioration. However, a complicated circuitry is essential to measure the resistive leakage current included in the total leakage current, and the difficult handling of the measurement makes few applications to the fields. In this paper, we propose a resistive leakage current measurement device which is composed of a current detection circuit and an analysis program operated on a microprocessor. The device samples the input leakage current waveform digitally, and discriminate the zero-cross and the peak point of the waveform to analyze the current amplitude vs. phase. The capacitive leakage current is then eliminated from the total leakage current by using an algorithm to extract the resistive leakage current only. Also, the device can be operated automatically and manually to analyze the resistive leakage current even when the leakage current waveform is distorted due to various types of arrester deterioration. To estimate the performance of the device, we carried out a test on ZnO blocks and lightning arresters. From the results, it is confirmed that the device could analyze most parameters needed for the arrester diagnostics such as total leakage current. resistive leakage current, and the $3^rd$ harmonic leakage current.

• Journal of the Korean Geotechnical Society
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• v.17 no.6
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• pp.225-233
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• 2001

Field model tests were performed to develop the grid-net landfill leachate leakage detection system using electrical resistance. Electric circuit tests were also carried out to investigate the expected electrical effects of grid-net electric circuit. The resistance of leaking point showed lower value than that of non leaking point. Grid-net leakage detection system was thought to be effective to locate the leachate leaking point. The measured electrical resistance along the wire including the leaking point was slightly reduced following the reduction of electrical resistance at the leaking point, which was explained by electric circuit test results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.10
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• pp.1445-1453
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• 2017

In this paper, we propose a fault detection model based on multi-layer neural network using data mining technique for faults due to boiler tube leakage in a thermal power plant. Major measurement data related to faults are analyzed using statistical methods. Based on the analysis results, the number of input data of the proposed fault detection model is simplified. Then, each input data is clustering with normal data and fault data by applying K-Means algorithm, which is one of the data mining techniques. fault data were trained by the neural network and tested fault detection for boiler tube leakage fault.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.7
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• pp.508-516
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• 2008

Fault detection and diagnosis(FDD) system is beneficial in equipment management by providing the operator with tools which can help find out a failure of the system. An experimental study has been performed on fault detection and diagnosis method for a water chiller. Bayes classifier, which is one of classical pattern classifiers, is adopted in deciding whether fault occurred or not. Failure modes in this study include refrigerant leakage, decrease in mass flow rate of the chilled water and cooling water, and sensor error of the cooling water inlet temperature. It is possible to detect and diagnose faults in this study by adopting FDD algorithm using only four parameters(compressor outlet temperature, chilled water inlet temperature, cooling water outlet temperature and compressor power consumption). Refrigerant leakage failure is detected at 20% of refrigerant leakage. When mass flow rate of the chilled and cooling water decrease more than 8% or 12%, FDD algorithm can detect the faults. The deviation of temperature sensor over $0.6^{\circ}C$ can be detected as fault.

• Investigative Magnetic Resonance Imaging
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• v.17 no.2
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• pp.149-153
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• 2013

Detection of cerebrospinal fluid leakage or exact localization of leakage site after spinal surgery is difficult on conventional imaging studies. We report two patients with surgery-related spinal CSF leakage detected on magnetic resonance (MR) myelography. They presented with severe headache after spinal surgeries, lumbar discectomy and excision of spinal meningioma, respectively. The sites of spinal CSF leakage in the patients were detected accurately on MR myelography, and the patients recovered from the postoperative CSF leakage after being treated with an epidural blood patch or reoperation. MR myelography may be effective in demonstrating the exact site of surgery-related spinal CSF leakage.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.3
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• pp.161-165
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• 2004

In this paper, we have designed the ground faults detection and interrupting controller at normal condition of AC 120v to 240v rating voltage. Ground faults in electrical network have the characteristics of low current, 60㎐ frequency to 2㎑frequency. The load condition are no load and 20A load. The trip level of the controller is 6㎃ with ground faults. The Controller algorithm is implemented using pic16c71 microprocessor.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.77-87
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• 2019

One of important concerns in information security is to control information flow. It is whether to protect confidential information from being leaked, or to protect trusted information from being tainted. In this paper, we present Piosk (Physical blockage of Information flow Kiosk) that addresses both the problems practically. Piosk can forestall and prevent the leakage of information, and defend inner tangible assets against a variety of malwares as well. When a visitor who carries a re-writable portable storage device, must insert the device into Piosk installed next to the security gate. Then, Piosk scans the device at the very moment, and detects & repairs malicious codes that might be exist. After that, Piosk writes the contents (including sanitized ones) on a new read-only portable device such as a compact disk. By doing so, the leakage of internal information through both insiders and outsiders can be prevented physically. We have designed and prototyped Piosk. The experimental verification of the Piosk prototype implementation reveals that, Piosk can accurately detect every malware at the same detection level as Virus Total and effectively prevent the leakage of internal information. In addition, we compare Piosk with the state-of-the-art methods and describe the special advantages of Piosk over existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.963-971
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• 2022

Water pipeline network in local and metropolitan area is buried underground, by which it is hard to know the degree of pipe aging and leakage. In this study, assuming various sensor combinations installed in the water pipeline network, the optimal algorithm was derived by predicting the water flow rate and pressure through artificial intelligence algorithms such as linear regression and neuro fuzzy analysis to examine the possibility of detecting pipe leakage according to the data combination. In the case of leakage detection through water supply pressure prediction, Neuro fuzzy algorithm was superior to linear regression analysis. In case of leakage detection through water supply flow prediction, flow rate prediction using neuro fuzzy algorithm should be considered first. If flow meter for prediction don't exists, linear regression algorithm should be considered instead for pressure estimation.