• 대한기계학회논문집
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• 제13권1호
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• pp.96-104
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• 1989

본 연구에서는 AE법에 의해 J$_{IC}$를 결정하는 것은 Takahashi등의 방법을 따르되 AE 실험결과를 토대로 이론을 전개하여 재료의 물성 곡선인 J-R곡선의 실험식과 재료 찢어짐 계수를 계산할 수 있는 실험식을 유도하며, 이렇게 구한 실험식을 불안정 파괴 조건에 적용하여 그 타당성을 검토한다.다.

• 대한기계학회논문집A
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• 제35권9호
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• pp.1131-1136
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• 2011

본 연구는 자동차용 CNG 연료탱크의 파열시험시 발생하는 음향방출변수의 분석에 관한 내용이다. 연료탱크의 복합재료 중앙부 표면에 150kHz 공진형 AE센서를 부착하여 파열시험시 발생하는 음향방출 신호를 획득하고, 가압유지시간 동안의 hit, amplitude, count, duration, risetime, signal strength 등과 같은 음향방출 변수들을 분석하였다. 음향방출 변수 중 total count, total signal strength가 연료탱크 손상정도를 평가하는데 유용한 변수임을 알 수 있었다.

• 비파괴검사학회지
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• 제10권1호
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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.

• 동력기계공학회지
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• 제2권3호
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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.

• 한국신뢰성학회지:신뢰성응용연구
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• 제13권2호
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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.

• 한국정밀공학회지
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• 제11권4호
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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.

• 한국재료학회지
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• 제17권5호
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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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• 제29권3호
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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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• 제37권2호
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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.

• 한국정밀공학회지
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• 제8권1호
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• pp.74-83
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• 1991

A study on the Correlation of Orthogonal Cutting Parameter (Cutting speed, Depth of cut, Feed Rate) and Acoustic Emission Signal. It is well known that acoustic emission (AE) is the emission of elastic wave resulting from the deformation and fracture of materials. This study estabished correlation of orthogonal cutting parameter and AE signal, and researched into in-process monitoring of tool wear and failure. The results are as follow; 1. AE RMS was under the influence of cutting speed but hardly influenced by depth of cut and feed rate. 2. AE RMS was under the influence of flank wear. 3. AE count rate increased by increased cutting speed. 4. AE RMS value was rapidly increased in 130 m flank wear.