• Geomechanics and Engineering
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• v.39 no.2
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• pp.157-170
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• 2024

In the present study, the acoustic emission characteristics of hard sedimentary sandstone with varying bedding dip angles were examined through uniaxial compression tests using a rock mechanics creep apparatus combined with an acoustic emission system. The deformation and failure behavior of the sandstone was analyzed by correlating acoustic emission parameters with stress over time. A damage constitutive model was developed, incorporating cumulative acoustic emission ringing counts as a key parameter, with time acting as the intermediary. The findings indicate that, despite the differences in bedding dip angles, the stress-strain curves of the samples follow a similar pattern throughout the loading process, passing through four distinct phases: compaction, elastic deformation, yielding, and post-peak failure. The fracture patterns of the sandstone are influenced by the dip angle of the bedding. Acoustic emission parameters, including the ringing count, cumulative ringing count, and energy, align with these four stages of the stress-strain curve. During the compaction and elastic deformation phases, acoustic emissions remain in a quite state, with only brief spikes at points of rapid stress change. In the unstable fracture stage, acoustic emissions become highly active, while they return to a quite state in the post-fracture stage. The RA value of the acoustic emission displays a banded pattern as time progresses, with areas of dense clustering. When the stress curve declines, RA values enter an active period, mainly associated with the generation of shear cracks. Conversely, during periods of smooth stress progression, RA values remain in a quiet state, primarily linked to the formation of tensile cracks. The time-based damage constitutive model for layered sandstone effectively captures the entire process of rock fracture development.

• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.1
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• pp.96-104
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• 1989

The behaviors of acoustic emission emitted in the tests of the fracture toughness and fracture stability are observed by using the specimens of aluminum 2024-T351 and 7039-T6 alloys. The empirical eqution of J-R curve is derived. It is demonstrated from the comparison of the fracture toughness obtained from J-R curve with that from ASTM standard E813-81 that the latter is larger than the former. The discontinuous point in the log-log graph of J-integral vs. total acoustic emission count is observed in between the two offset lines referred from ASTM standard E813-81, but it's physical meaning is uncretain. An empirical material tearing modulus is derived in terms of the total acoustic emission count and proved to be valid in fracture instability test.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.9
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• pp.1131-1136
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• 2011

This study is performed on the acoustic emission parameters involved in a burst test for a CNG-vehicle fuel tank. A resonant AE sensor with a central frequency of 150 kHz was attached on the composite materials in the center of the fuel tank. The analysis of AE parameters such as hit, amplitude, count, duration, risetime, and signal strength during load holding was performed. The total count and total signal strength are effective tools for the damage evaluation of a CNG fuel tank.

• Journal of the Korean Society for Nondestructive Testing
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• v.10 no.1
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• pp.65-72
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• 1990

Comparison of acoustic emission, ultrasonic testing and crack gauge in 3-point bending testing have been studied. As the results, COD is indirectly assumed by strain gauge rate and grid pitch width when crack gauge grid is out. Acoustic emission is qualitatively able to measure crack growth by total count but ultrasonic testing has a difficulty in measuring it because of echo height fluctuation according to the change and pressure of UT. probe.

• Journal of Power System Engineering
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• v.2 no.3
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• pp.49-54
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• 1998

This paper is investigated of hardness and adhesiveness of plasma sprayed coating steels by AE(Acoustic Emission) testing when loading a tensile. AE Parameters used are Event, Count, Energy and Amplitude. Test specimens are carbon steel(S45C) with sprayed coating layers of Ni-4.5wt.%Al(bond coating) and $TiO_2$(top coating), and carry out heat treatment at $800^{\circ}C\;and\;1000^{\circ}C$, respectively. The micro-hardness of the heat treatment specimen have been improved more than that of non-heat treatment. On the tensile test, the process and occurence of the exfoliation of the sprayed coating layer can be estimated by AE Characteristics of AE parameters, such as event, count, amplitude and energy, on the layer exfoliation are shown the similar aspects. The exfoliation of bond coating occure at about 20% of strain and top coating is about 5% of strain.

• Journal of Applied Reliability
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• v.13 no.2
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• pp.129-140
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• 2013

As a fundamental experimental study for reliability improvement of lithium ion secondary battery, degradation mechanism was investigated by microscopic observation and acoustic emission monitoring. Microstructural observation of the decomposed battery after cycle test revealed mechanical and chemical damages such as interface delamination, microcrack of the electrodes, and solid electrolyte interphase (SEI). Acoustic emission (AE) signal was detected during charge and discharge of lithium ion battery to investigate relationships among cumulative count, discharge capacity, and microdamages. With increasing number of cycle, discharge capacity was decreased and AE cumulative count was observed to increase. Observed damages were attributed to sources of the detected AE signals.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.69-76
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• 1994

AE(Acoustic Emission) signal is correlated to workpiece material, cutting conditions and tool geometry during metal cutting. The relationship between AE signal and cutting parameters can be obtained by theoretical model and experiments. The value of CR(Count Rate) is nearly constant in stable cutting, but when the chatter vibration occours, the value of CR is rapidly increased due to the vibration deformation zone. By experimental signal processing of AE, it is more effective than by RMS(Root Mean Square) measurement to detect the threshold of chatter vibration by CR measurement.

• Korean Journal of Materials Research
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• v.17 no.5
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• pp.239-243
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• 2007

The evaluation and comparison have been made for the EMI noise which was included in the signal from the sensors in the acoustic emission testing for the bottom plate of ground tank at full. The EMI signal has been classified into two types. One is the signal with very short AE count, and this signal possibly can be filtered by front end filter setting of the channel count with low level of 4 and high level of $10^8$. The other EMI signal occurred from CH 1, CH 3 and CH 10, and had high and constant duration with high energy and count (maximun duration > $10^5\;{\mu}s$), and has characteristic gradient of accumulation amplitude distribution. This signal should be removed in the AE signal evaluation by filtering, because this may affect to the total gradient.

• Journal of Biosystems Engineering
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• v.29 no.3
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• pp.261-266
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• 2004

This study was Performed to classify the acoustic emission(AE) signal due to surface cracking and moisture movement in the flat-sawn boards of oak(Quercus Variablilis) during drying using the principal component analysis(PCA) and artificial neural network(ANN). To reduce the multicollinearity among AE parameters such as peak amplitude, ring-down count event duration, ring-down count divided by event duration, energy, rise time, and peak amplitude divided by rise time and to extract the significant AE parameters, correlation analysis was performed. Over 96 of the variance of AE parameters could be accounted for by the first and second principal components. An ANN analysis was successfully used to classify the Af signals into two patterns. The ANN classifier based on PCA appeared to be a promising tool to classify the AE signals from wood drying.

• Geomechanics and Engineering
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• v.37 no.2
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• pp.149-166
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• 2024

The acoustic emission (AE) technique is utilized to estimate the rock failure status in underground spaces. Understanding the AE characteristics under loading conditions is essential to ensure the reliability of AE monitoring. The AE characteristics depend on the material properties (p-wave velocity, density, UCS, and Young's modulus) and damage stages (stress ratio) of the target rock mass. In this study, two groups of granite specimens (based on the p-wave velocity regime) were prepared to explore the effect of material properties on AE characteristics. Uniaxial compressive loading tests with an AE measurement system were performed to investigate the effect of the rock properties using AE indices (count index, energy index, and amplitude index). The test results were analyzed according to three damage stages classified by the stress ratio of the specimens. Count index was determined to be the most suitable AE index for evaluating rock mass stability.