• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.6
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• pp.35-42
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• 2000

In this paper, AE(Acoustic Emission) signals detected from the growth of the electrical tree in an epoxy resin under ac high-voltage application were analysed to diagnose the insulation deterioration of cast-resin power transformer. Frequency spectra of AE signals generated from the magnetizing and the load currents in the actual operating cast-resin power transformer of 500[kVA] under distribution system of 22.9[kV] were also analysed to distinguish the AE signals due to void discharges from the magnetic circuit noises in the core of the transformer. As the experimental results, we could distinguish the AE signals whether those signals were caused due to the void discharges or due to the magnetic circuit noises by analyzing the frequency spectrum of AE signals. The frequency spectra of AE signals generated from the cast-resin power transformer in operation due to both the magnetizing and the load currents appeared in the range of 40-120[kHz], but the frequency band of AE signals emitted from the void discharges in an epoxy resin sample was about 50[kHz] to 230[kHz].

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.4
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• pp.95-99
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• 2004

In this study, the leak detection technique of pressure vessel by using acoustic emission(AE) signal is suggested experimentally. The leak of pressure vessel is located at the welding line due to welding defects. we measured the AE signal using Rl5I sensor, and examined the AE parameters in leak condition. It is investigated that the mean value of AE signal is dependent on leak source location. So the absolute mean value of AE signal is adopted as dominant AE parameter. We proposed leak detection algorithm using AE signal mean value for monitoring the leak source location.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1995.03a
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• pp.174-180
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• 1995

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.100.1-100.1
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• 2005

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.4
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• pp.51-58
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• 2010

Recently, aerospace structures have lightweight trend in order to reduce the cost of fuel and system, Carbon Fiber Reinforced Plastic (CFRP) can give the ability to reduce weight at 20~50% as the substitution of metal alloy, and there are advantages such as high Non-rigid, specific strength and anti-corrosion, but it is difficult to prove its destruction properties due to heterogeneous structure and anisotropy. In this study we designed specimen, inducing distinguishing destructions of material (for example, matrix crack, fiber breakage, and delamination) by using the Carbon Fiber Reinforced Plastic (CFRP) which is used in a real aircraft, to apply acoustic emission technique to aerospace structures. And we gained data via tensile testing and acoustic emission technique, from which each fault signal was classified respectively by using AE parameters and waveform.

• Composites Research
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• v.16 no.1
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• pp.26-33
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• 2003

Utilizing a thermo-acoustic emission (AE) technique, a study on detection and evaluation of microfractures in cross-ply laminate composites was performed. Fiber breakages and matrix fractures formed by a cryogenic cooling at $-191^{\circ}C$ were observed with ultrasonic C-scan, optical and scanning electron microscopy. Those microfractures were monitored in a non-destructive in-situ state as three different types of thermo-AE signals classified on the basis of Fast-Fourier Transform and Short-Time Fourier Transform. Thus, it was concluded that real-time estimation of microfracture processes being formed during cryogenic cooling could be accomplished by monitoring such different types of thermo-AEs in each time-stage and then by analyzing thermo-AE behaviors for the respective AE types on the basis of the AE signal analysis results obtained during thermal heating and cooling load cycles.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.58-63
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• 2004

This study is to investigate a fracture characteristics of carbon fiber reinforced plastics (CFRP) under the tensile loading as a function of acoustic emission (AE) according to the frequency analysis (transient mode) and AE source location (location mode). It was found that the fracture mechanism of AE frequency analysis was a useful tool for the estimation of different type of fracture in CFRP, i.e., matrix(epoxy resin) cracking, delamitation and fiber breakage same as AE amplitude distribution.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.4
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• pp.220-230
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• 2006

Fracture behavior of a monolithic PZT and a plate-type piezoelectric composite actuator (PCA) has been investigated under a bending load at three points by an acoustic emission (AE) monitoring. AE signal from a monolithic PZT at the maximum bending load shows the characteristics of high amplitude and long duration with a low frequency band of $100{\sim}230kHz$ which is confirmed by fast Fourier transform (FFT). For a PCA, it is concluded that AE signals with high amplitude over 80dB and low dominant frequency band of $170{\sim}223kHz$ emitted in the stage I are due to the brittle fracture in the PZT layer and the delamination between the PZT layer and the adjacent fiber composite layer. Based on the above analysis of AE behavior and damage observations with an optical microscopy and a scanning electron microscopy, AE characteristics related to fracture behavior of asymmetrically laminated PCA have been elucidated.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.220-226
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• 2003

This paper presents the result of an investigation on the application of the acoustic emission method to the monitoring of fatigue crack initiation, growth and track location in welded joints. Fatigue test was carried out for a typical fillet welded joint of ship structure. AE parameter such as ring down count was analyzed in time domain and crack locations were examined by source location and cluster option which is one of the functions of AE signal processor The usability of AE mettled was confirmed for the detection of the initiation and location of through crack.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.37-43
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• 2005

Real time monitoring of exit burr formation is critical in manufacturing automation. In this paper, acoustic emission (AE) was used to detect the burr formation during drilling. By using wavelet transform (WT), AE data were compressed without unnecessary details. Then the transformed data were used as selected features (inputs) of a back-propagation artificial neural net (ANN). In order to validate the in process AE monitoring system, both WT-based ANN and cutting condition (cutting speed, feed, drill diameter, etc.) based ANN outputs were compared with experimental data.