• Journal of the Korean Society of Safety
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• v.19 no.1
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• pp.31-37
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• 2004

The mechanical strength and crack propagation of plain woven carbon fiber fabric laminate composites are examined by acoustic emission(AE). AE signals are measured during the tensile test and fracture tests. Thus, the relationship between AE signal and load-displacement curves and crack extension length are shown. Also the fracture mechanisms in terms of AE characteristics are discussed in viewpoint of crack propagation behavior.

• Proceedings of the KIEE Conference
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• 2004.07c
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• pp.1748-1750
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• 2004

This paper deals with the detection method of the Quench phenomenon for superconducting magnet using the Acoustic Emission (AE) sensor. AE sensor is the elements, which is used to change the Acoustic signal to the voltage value. This signal may be used to detect whether the superconducting magnet has been at the Quench state or not. Recently, the development of the Quench detection technique, which is the using voltage and current signals, fiber-optic sensor, and so on, for the superconducting applications is widely studying. This method for the Quench detection of the superconducting magnet is also studying at some kinds of institute in Japan and the united state. Because of the large-scale superconducting magnet like International Thermonuclear Experimental Reactor(ITER) is charged a lot of energy, when the Quench phenomenon is being at the superconducting magnet it is happen to the problem of the protection for the applications. In this paper, we concluded that the Quench detection was possible when the mechanical stress by means of the local heat is generated at the part of inside superconducting magnets.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.687-692
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• 2008

In a nuclear power plant, loose part monitoring and its diagnostic technique is one of the major issues for ensuring the structural integrity of the reactor system. Typically, accelerometers are mounted on the surface of a reactor vessel to localize impact location caused by the impact of metallic substances on the reactor system. However, in some cases, the number of the accelerometers is not enough to estimate the impact location precisely. In such a case, one of alternative plan is to utilize another type sensors that can measure the vibration of the reactor structure even though the measuring frequency ranges are different from each others. The AE sensors installed on the reactor structure can be utilized as additional sensors for loose part monitoring. In this paper, we proposed a new method to estimate impact location by using both accelerometer signal and AE signal, simultaneously. The feasibility of the proposed method is verified by an experiment. The experimental results demonstrate that we can enhance the reliability and precision of the loose part monitoring.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.3
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• pp.326-333
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• 2010

In this study, DAQ and TRA modules were applied to the CFRP single specimen testing method using AE. A method for crack identification in CFRP specimens based on k-mean clustering and wavelet transform analysis are presented. Mode I on DCB under vertical loading and mode II on 3-points ENF testing under share loading have been carried out, thereafter k-mean method for clustering AE data and wavelet transition method per amplitude have been applied to investigate characteristics of interfacial fracture in CFRP composite. It was found that the fracture mechanism of Carbon/Epoxy Composite to estimate of different type of fractures such as matrix(epoxy resin) cracking, delamination and fiber breakage same as AE amplitude distribution using a AE frequency analysis. In conclusion, the presented results provide a foundation for using wavelet analysis as efficient crack detection tool. The advantage of using wavelet analysis is that local features in a displacement response signal can be identified with a desired resolution, provided that the response signal to be analyzed picks up the perturbations caused by the presence of the crack.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.11
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• pp.1143-1149
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• 2008

In a nuclear power plant, loose part monitoring and its diagnostic technique is one of the major issues for ensuring the structural integrity of the reactor system. Typically, accelerometers are mounted on the surface of a reactor vessel to localize impact location cavsed by the impact of metallic substances on the reactor system. However, in some cases, the number of the accelerometers is not enough to estimate the impact location precisely. In such a case, one of alternative plan is to utilize another type sensors that can measure the vibration of the reactor structure even though the measuring frequency ranges are different from each others. The AE sensors installed on the reactor structure can be utilized as additional sensors for loose part monitoring. In this paper, we proposed a new method to estimate impact location by using both accelerometer signal and AE signal, simultaneously. The feasibility of the proposed method is verified by an experiment. The experimental results demonstrate that we can enhance the reliability and precision of the loose part monitoring.

• Smart Structures and Systems
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• v.16 no.1
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• pp.67-79
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• 2015

Acoustic emission analysis is an effective technique for monitoring the evolution of damage in a structure. An experimental analysis on a set of reinforced concrete beams under flexural loading was carried out. A mixed AE analysis method which used both parameter-based and signal-based techniques was presented to characterize and identify different failure mechanisms of damage, where the signal-based analysis was performed by using the Hilbert-Huang transform. The maximum instantaneous energy of typical damage events and the corresponding frequency characteristics were established, which provided a quantitative assessment of reinforced concrete beam using AE technique. In the bending tests, a "pitch-catch" system was mounted on a steel bar to assess bonding state of the steel bar in concrete. To better understand the AE behavior of bond-slip damage between steel bar and concrete, a special bond-slip test called pullout test was also performed. The results provided the basis of quantitative AE to identify both failure mechanisms and level of damages of civil engineering structures.

• Journal of the Korean Society for Nondestructive Testing
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• v.16 no.1
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• pp.34-45
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• 1996

The signal pattern recognition program which can perform signal acquisition and processing, the extraction and selection of features, the classifier design and the evaluation, is developed and applied to the classification of artificial defects in the weld zone of Austenitic STS304. The neural network classifier is compared with the linear discriminant function classifier and the empirical Bayesian classifier. The signal through a broadband sensor is compared with that through a resonance type sensor. In recognition rate, the neural network classifier is best, and the signal through a broadband sensor is better.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.10
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• pp.907-911
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• 2007

This paper dealt with the frequency spectrum analysis of acoustic signal produced by partial discharge (PD) in insulation oil and the positioning of PD occurrence to apply in diagnosis of oil insulated transformers. Three types of electrode system ; the needle-plane, the plane-plane, and the wire-wire structure were assembled to simulate partial discharges in oil insulated transformers. A low-noise amplifier and a decoupling circuit were designed to detect acoustic signal with high sensitivity The frequency spectrum of the acoustic signal were 50 kHz ${\sim}$ 260 kHz in the needle-plane, 50 kHz ${\sim}$ 250 kHz in the plane-plane, and 45 kHz${\sim}$195 kHz in the wire-wire electrode system. Their peak frequencies were 145 kHz, 130 kHz and 114 kHz, respectively The position of PD occurrence was calculated by the time difference of arrival (TOA) using three acoustic emission (AE) sensors, and we could find the position within the error of 1 % in the experimental apparatus.

• Journal of Korean Society of Steel Construction
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• v.9 no.3 s.32
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• pp.287-300
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• 1997

In this study, an effective application method of AE technique for the detection of fatigue crack in multi-girder steel bridges has been proposed. The applicability has been examined through the laboratory works with bridge model. The proposed analytical method which evaluates the remaining fatigue lives of structural members may improve the rational determination of the priority of inspection for structural members assuming to have fatigue cracks. Laboratory tests for the application of AE technique to steel girder bridges show that the frequency bands of traffic noise are in the range between 10 show that the frequency bands of traffic noise are in the range between 100~200 kHz and the AE signal raised from fatigue cracks is concentrated around 400~500 kHz. Therefore. R30 sensor is proved to be the most suitable for the detection of cracks in steel girder bridges. A linear proportionality between the crack propagation and the frequency of AE signals has been obtained. In addition, an economic and effective source location method for steel girder bridges was studied through experiments.

• Smart Structures and Systems
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• v.18 no.5
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• pp.1063-1085
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• 2016

Taking advantage of the high sensitivity and long-distance detection capability of acoustic emission (AE) technique, this paper focuses on the crack detection in rail head, which is one of the most vulnerable parts of rail track. The AE source location and noise cancellation were studied on the basis of practical rail profile, material and operational noise. In order to simulate the actual AE events of rail head cracks, field tests were carried out to acquire the AE waves induced by pencil lead break (PLB) and operational noise of the railway system. Wavelet transform (WT) was first utilized to investigate the time-frequency characteristics and dispersion phenomena of AE waves. Here, the optimal mother wavelet was selected by minimizing the Shannon entropy of wavelet coefficients. Regarding the obvious dispersion of AE waves propagating along the rail head and the high operational noise, the wavelet transform-based modal analysis location (WTMAL) method was then proposed to locate the AE sources (i.e. simulated cracks) respectively for the PLB-induced AE signals with and without operational noise. For those AE signals inundated with operational noise, the Hilbert transform (HT)-based noise cancellation method was employed to improve the signal-to-noise ratio (SNR). Finally, the experimental results demonstrated that the proposed crack detection strategy could locate PLB-simulated AE sources effectively in the rail head even at high operational noise level, highlighting its potential for field application.