• Journal of the Korean Institute of Gas
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• v.17 no.2
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• pp.70-77
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• 2013

The present study has been carried out to analyze the effect of steam hammering on the steam piping system including the final superheater, the high pressure turbine, check valve and the first reheater by sudden stoping of main stop valve in a power plant. For the present steam hammering analysis, the well known Flowmaster software has been used to model the steam piping system and the time dependent characteristics of pressure and steam mass flow rate has been conducted. Using the result of the unsteady pressure and steam mass flow rate, the forces acting on the elbows in the piping system has been derived. From the present analysis, it has been elucidated that the elbow just before the main stop valve and the elbow near the connection pipe between bypass pipe and check valve had the largest force among the elbows in the steam piping system. The structural safety diagnostics study on the elbow and the supporting structures of the steam piping system of a power plant will be conducted in the future by the present results of the forces acting on the elbow.

• Journal of Power System Engineering
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• v.12 no.2
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• pp.18-22
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• 2008

A few intake stations have vibration problems caused by pipes. The vibration transffered from pipes excites building severely. Therefore, the crack is generated on building wall and people who work at intake station are damaged. In this paper, the vibration is measured and analysis is carried out for pipes at intake station in order to identify the usefulness and effectiveness of the solution proposed for pipe resonance avoidance. According to the result of analysis, the vibration of pipes is reduced by bellows.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1371-1374
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• 2007

A few intake stations have vibration problems caused by pipes. The vibration transffered from pipes excites building severely. Therefore, the crack is generated on building wall and people who work at intake station are damaged. In this paper, the vibration is measured and analysis is carried out for pipes at intake station in order to identify the usefulness and effectiveness of the solution proposed for pipe resonance avoidance. According to the result of analysis, bellows is reduced the vibration of pipes.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.49-60
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• 2011

• Proceedings of the Korean Vacuum Society Conference
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• 2006.08a
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• pp.113-113
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• 2006

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.4
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• pp.323-330
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• 2008

High cycle bending fatigue of socket welded small bore pipe was characterized, and also the fatigue crack initiation of small bore pipe was monitored in situ by the acoustic emission (AE) technique. The STS 316L stainless steel specimens were prepared by gas tungsten arc welding (GTAW) process having the artificial defect (i.e., lack of penetration) and defect free at the root. The fatigue failure was occurred at the loc for high stress and root for relatively low stress. The crack initiation cycles ($N_i$) was defined to the abrupt increase in AE counts during the fatigue test, and then the cracks were observed by the radiographic test and electron microscope before and after the fatigue crack initiation cycles. The socket welded pipe damaged by bending fatigue was studied regarding the welding defect, failure mode, and crack initiation cycles for the diagnosis and monitoring.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.46-52
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• 2024

The structural safety of expansion joints for piping systems has been drawing attention owing to ruptures and leaks of water pipes caused by earthquakes and road subsidence at soft ground. In general, metal bellows are installed as expansion joints to prevent various damages in the piping system. In this study, the seismic performance of a valve chamber system was evaluated by performing earthquake shaking table tests. To validate the benefits to structural safety of metal bellows in connecting steel pipes to valve chambers, the seismic tests were conducted on expansion joints (bellows) and general pipping, and the results were compared for durability. Strain gauges were attached to measure the effects of the input motion. As a result of the shaking table test, it was confirmed that the strain of the valve chamber structure and inflow or outflow steel pipes were decreased in 1/100, 1/20 by applied to the expansion joints.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.6
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• pp.171-178
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• 2010

Pipeline structure is one of core underground infrastructure which transports primary sources. Since the almost pipeline structures are placed underground and connected each other complexly, it is difficult to monitor their structural health condition continuously. In order to overcome this limitation of recent monitoring technique, recently, a Ubiquitous Sensor Network (USN) system based on on-line and real-time monitoring system is being developed by the authors' research group. In this study, real-time pipeline health monitoring (PHM) methodology is presented based on electromechanical impedance methods using USN. Two types of damages including loosened bolts and notches are artificially inflicted on the pipeline structures, PZT and MFC sensors that have piezoelectric characteristics are employed to detect these damages. For objective evaluation of pipeline conditions, Damage metric such as Root Mean Square Deviation (RMSD) value was computed from the impedance signals to quantify the level of the damage. Optimal threshold levels for decision making are estimated by generalized extreme value(GEV) based statistical method. Throughout a series of experimental studies, it was reviewed the effectiveness and robustness of proposed PHM system.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.1
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• pp.166-173
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• 2014

A noncontact nondestructive testing (NDT) method is proposed to detect the damage of pipeline structures and to identify the location of the damage. To achieve this goal, a scanning laser source actuation technique is utilized to generate a guided wave and scans a specific area to find damage location more precisely. The ND: YAG pulsed laser is used to generate Lamb wave and a piezoelectric sensor is installed to measure the structural responses. The measured responses are analyzed using three dimensional Fourier transformation (3DFT). The damage-sensitive features are extracted by wavenumber filtering based on the 3D FT. Then, flaw imaging techniques of a pipeline structures is conducted using the damage-sensitive features. Finally, the pipes with notches are investigated to verify the effectiveness and the robustness of the proposed NDT approach.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.184-192
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• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.