• Journal of Korean Society of Environmental Engineers
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• v.27 no.10
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• pp.1065-1071
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• 2005

Many techniques of leak detection in pipeline systems have developed based on the propagation wave speeds and wave attenuation. In this paper, the transient analysis methodology is used for calculating the wave speed in the plastic pipe and a frequency analysis methodology is developed for leakage detection in water pipe networks. Data acquisition system for pressurized pipeline system were designed md fabricated to obtain high frequency pressure data. The methodology properly handles the unavoidable uncertainties in measurement and modeling error. Based on information from head pressure test data, it provides leak prediction capability from the transient events with leakage.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.3122-3125
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• 2021

Electromagnetic vortex flowmeter is a new type of instrument for detecting leakage of steam generator, and the signal processing method based on the envelope to calculate energy ratio can effectively detect bubbles in sodium flow. The signal processing method is not affected by changes in the amplitude of the sensor output signal, which is caused by changes in magnetic field strength and other factors. However, the detection sensitivity of the electromagnetic vortex flowmeter is reduced. To this end, a signal processing method based on inverse Fourier transform to calculate energy ratio is proposed. According to the difference between the frequency band of the bubble noise signal and the flow signal, only the amplitude in the frequency band of the flow signal is retained in the frequency domain, and then the flow signal is obtained by the inverse Fourier transform method, thereby calculating the energy ratio. Using this method to process the experimental data, the results show that it can detect 0.1 g/s leak rate of water in the steam generator, and its performance is significantly better than that of the signal processing method based on the envelope to calculate energy ratio.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1677-1688
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• 2020

In the sodium-cooled fast reactor, the steam generator is a heat exchange device between sodium and water, which may cause leakage, resulting in a sodium-water reaction accident, which in turn affects the safe operation of the entire nuclear reactor. To this end, the electromagnetic vortex flowmeter is used to detect leakage of the steam generator and its signal processing method is studied in this paper. The hydraulic experiment was carried out by using water instead of liquid sodium, and the sensor output signal of the electromagnetic vortex flowmeter under different gas injection volumes was collected. The bubble noise signal is reflected by the base line of the sensor output signal. According to the relationship between the proportion of the bubble noise signal in the sensor output signal and the gas injection volume, a signal processing method based on the energy ratio calculation is proposed to detect whether the water contains bubbles. The gas injection experiment of liquid sodium was conducted to verify the effectiveness of the signal processing method in the detection of bubbles in sodium, and the minimum detectable leak rate of water in the steam generator was detected to be 0.2 g/s.

• 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.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.961-969
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• 2009

Water absorption in water-cooled generator stator windings can cause serious accidents such as insulation breakdown and it brings a generator to the unexpected sudden outage. Accordingly, it is important to diagnose the water absorption of them in the effective operation of power plant. Especially, the capacitance value which is measured for diagnosis is very small so the special diagnosis methods like stochastic theory are needed. KEPRI developed the water absorption test equipment and diagnosis technology for them. In this paper we propose that water absorption test of generator stator windings using probability distributions. The proposed diagnosis technology is applied to the real system and the results of water absorption test for stator windings are agreed to them of water leak test.

• 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.

• Ocean Systems Engineering
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• v.8 no.1
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• pp.41-55
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• 2018

Accidental oil and gas leak is a critical concern for the offshore industry because it can lead to severe consequences and as a result, it is imperative to evaluate the probabilities of occurrence of the consequences of the leakage in order to assess the risk. Event Tree Analysis (ETA) is a technique to identify the consequences that can result from the occurrence of a hazardous event. The probability of occurrence of the consequences is evaluated by the ETA, based on the failure probabilities of the sequential events. Conventional ETA deals with events with crisp failure probabilities. In offshore applications, it is often difficult to arrive at a single probability measure due to lack of data or imprecision in data. In such a scenario, fuzzy set theory can be applied to handle imprecision and data uncertainty. This paper presents fuzzy ETA (FETA) methodology to compute the probability of the outcomes initiated due to oil/gas leak in an actual offshore-onshore installation. Post FETA, sensitivity analysis by Fuzzy Weighted Index (FWI) method is performed to find the event that has the maximum contribution to the severe sequences. It is found that events of 'ignition', spreading of fire to 'equipment' and 'other areas' are the highest contributors to the severe consequences, followed by failure of 'leak detection' and 'fire detection' and 'fire water not being effective'. It is also found that the frequency of severe consequences that are catastrophic in nature obtained by ETA is one order less than that obtained by FETA, thereby implying that in ETA, the uncertainty does not propagate through the event tree. The ranking of severe sequences based on their probability, however, are identical in both ETA and FETA.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.810-813
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• 2004

한해 누수로 인하여 많은 양의 상수가 소실되고 있어 국가 재정낭비를 초래하고 있다. 이는 관의 노후화와 지반침하에 의한 파이프의 파손 둥 여러 요인에 의해 발생하는 것으로 누수를 예측하여 탐지하는 것은 매우 어렵다. 현재 누수를 탐지하는 방법은 여러 가지가 있지만 현실적인 제약과 경험자의 주관적인 판단에 의존하기 때문에 정확한 누수 위치를 찾을 수가 없었다. 본 논문에서는 종래의 누수탐지 방법의 단점을 획기적으로 보완하여 지하에 매설된 상수도 관망을 실시간으로 모니터링 할 수 있는 누수탐지 모니터링 시스템을 제안하였다 또한 제안된 시스템을 GIS상에서 실험함으로서 효율성과 정확성을 입증하였다.

• Journal of Korea Water Resources Association
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• v.46 no.10
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• pp.969-976
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• 2013

Leakage in water distribution system causes social and economic losses by direct water loss into the ground, and additional energy demand for water supply. This research suggests a leak detection model of using adaptive Kalman filtering on real-time data of pipe flow. The proposed model takes into account hourly and daily variations of water demand. In addition, the model's prediction accuracy is improved by automatically calibrating the covariance of noise through innovation sequence. The adaptive Kalman filtering shows more accurate result than the existing Kalman method for virtual sine flow data. Then, the model is applied to data from two real district metered area in JE city. It is expected that the proposed model can be an effective tool for operating water supply system through detecting burst leakage and abnormal water usage.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.1
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• pp.44-51
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• 1999

This paper proposes a new approach of plant fault diagnosis which is based on detecting the characteristic pattern signals and associating them with the corresponding faults. The new approach does not require analytic modeling of the target system but best reflects the expertise embedded in the experienced human operation by mimicking them in a systematic way. This paper intends to illustrate the feasibility of the proposed by developing the algorithms to detect and estimate the typical characteristic pattern signals, I. e., oscillatory patterns, and applying them to the diagnosis of various faults of a 500MW boiler control system including tube rupture, feed-water leak, and controller failure.