• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.3
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• pp.15-21
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• 1996

This study is focused on the prediction of appropriate tool life by clarifying the correlation between progressive tool wear and AE(Acoustic Emission) signals, while cutting stainless steel by end mill on the machining center. The results of this study were that RMSAE tends to increase linearly along with the increase of the cutting speed, and it was more sensitive to depth of cut than to the variation of feed rate at the same cutting conditions, and RMSAE increases around 0.21mm flank wear hereby AE-HIT also increases. AE signals depend upon tool wear and fracture from the above results. Therefore, the AE signals can be utilized in order to monitor the tool condition.

• Korean Journal of Materials Research
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• v.3 no.4
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• pp.361-371
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• 1993

Among the various test methods for stress corrusiun cracking(SCC) susceptibility evaluatiun, the slow stram rate test(SSHT) method is a rapid and effective nwthod to evaluate the SCC susceptibility of metal in relatively short time. But it is very difficult to analyze the microfracture behaviors in SCC process by using the test(SSRT) method only. Up to now, it has been well known that the acoustic emission(AE) test is the effective technique to monitor the microcrack initiation and propagation in material fracture pmcess. Therefore. in this paper, we analyzed the correlation between the see process and the characteristics of AE signal by using the SSHT and the AE test. According to the test results. the AE signals produced from the material microfracture were clearly depended on the test environment. The AE signal characteristics generated during see process in synthetic sea water were comparatively greater than those. in air. In addition, the SCC behaviors could be definitely evaluated by the amplitude parameter of AE signals.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.1
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• pp.68-76
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• 2011

Acoustic emission(AE) has emerged as a powerful nondestructive tool to detect any further growth or expansion of preexisting defects or to characterize failure mechanisms. Recently, this kind of technique, that is an in-situ monitoring of inside damages of materials or structures, becomes increasingly popular for monitoring the integrity of large structures like a huge wind turbine blade. Therefore, it is required to find a symptom of damage propagation before catastrophic failure through a continuous monitoring. In this study, a new damage location method has been proposed by using signal mapping algorithm, and an experimental verification is conducted by using small wind turbine blade specimen; a part of 750 kW real blade. The results show that this new signal mapping method has high advantages such as a flexibility for sensor location, improved accuracy, high detectability. The newly proposed method was compared with traditional AE source location method based on arrival time difference.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.1
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• pp.48-57
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• 2007

The fatigue crack growth behavior of a cracked and patch-repaired Ah2024-T3 panel has been monitored by acoustic emission(AE). The overall crack growth rate was reduced The crack propagation into the adjacent hole was also retarded by introducing the patch repair. AE signals due to crack growth after the patch repair and those due to debonding of the plate-patch interface were discriminated by usiag the principal component analysis. The former showed high center frequency and low amplitude, whereas the latter showed long rise tine, low frequency and high amplitude. This type of AE signal recognition method could be effective for the prediction of fatigue crack growth behavior in the patch-repaired structures with the aid of AE source location.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.1
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• pp.112-122
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• 1995

본 연구에서는 절삭공구가 채터진동을 일으킬때 AE(Acoustic Emission) 신호와 어떤관계가 있는지를 실험적으로 연구하였다. 모달분석을 통하여 절삭공구의 고유진동수 및 모우드형상을 구하였으며, 실제 절삭실험에서는 이송방향 및 절삭방향의 가속도를 계측하여 위상치를 결정하었다. AE신호와 두 가속도 와의 관계를 알기위하여 AE 실험을 하였다. AE신호의 폭발점은 대개 Lissajous loop의 방향전환점에서 관찰 되었다.

• 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].

• Tunnel and Underground Space
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• v.34 no.2
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• pp.169-184
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• 2024

This study investigates acoustic emission (AE) and micro-deformation characteristics of circular openings through biaxial compression experiments. The experimental results showed a significant increase in the frequency, count, energy, and amplitude of AE signals immediately before damage occurred in the circular opening. The differences in frequency and count between before and after damage initiation were significantly pronounced, indicating suitable factors for identifying damage occurrence in circular openings. The results for digital image correlation (DIC) technique revealed that micro-deformation was concentrated around the openings, as evidenced by the spatial distribution of strain. In addition, spalling was observed at the end of the experiments. The AE and micro-deformation characteristics presented in this study are expected to serve as fundamental data for evaluating the stability of underground openings and boreholes for deep subsurface projects.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.17 no.4
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• pp.42-47
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• 2009

Recently, the wide range of the composite materials is used for the making airplanes, trains and automobiles body for the lightweight. Despite having complex structures, composite materials usually have well defined mechanical characteristics. However, composite materials are difficult to understand the fracture mechanism clearly by simple mechanical test. Nondestructive evaluation (NDE) combined with mechanical testing can play a more important role and especially Acoustic Emission Testing (AET) would become known to be a useful tool to assess damage and fracture behavior of composites. In this study The experiment was performed to acquire the acoustic emission signal during tensile test using unidirectional CFRP specimen and the data was analyzed the acoustic emission parameters with the waveform.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.532-538
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• 2002

This study was performed to classify the fatigue crack opening and closure for three kinds of aluminum alloy using principal component analysis (PCA). Fatigue cycle loading test was conducted to acquire AE signals which come from different source mechanisms such as crack opening and closure, rubbing, fretting etc. To extract the significant feature from AE signal, correlation analysis was performed. Over 94% of the variance of AE parameters could accounted for the first two principal components. The results of the PCA on AE parameters showed that the first principal component was associated with the size of AE signals and the second principal component was associated with the shape of AE signals. An artificial neural network (ANN) an analysis was successfully used to classify AE signals into six classes. The ANN classifier based on PCA appeared to be a promising tool to classify AE signals for fatigue crack opening and closure.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.1
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• pp.39-55
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• 2022

This study carried out the laboratory tests for AE signal attenuation to determine the attenuation coefficient (α) of silo concrete in Gyeongju low and intermediate-level disposal environments. The concrete samples were prepared by satisfying the concrete mixing ratio used in the Gyeongju disposal silo, and these samples were additionally exposed depending on the temperature conditions and saturation and, dry condition. As a result of attenuation tests according to the transmission distance on three concrete specimens for each disposal condition, the AE amplitude and absolute energy measured on the saturated concrete were higher than that of the dry concrete in the initial range of the signal transmission distance, but the α of the saturated concrete was higher than that of the dry concrete. Regardless of the saturation and dry conditions, the α tended to decrease as the temperature increases. The α had a more major influence on the saturation and dry condition than the temperature condition, which means that the saturation and dry condition is the main consideration in measuring the signal attenuation of a concrete disposal structure. The α of concrete in the disposal environment expect to be used to predict the integrity of silos concrete in Gyeongju low and intermediate-level disposal environments by estimating the actual AE parameter values at the location of cracks and to determine the optimum location of sensors.