• 한국재료학회지
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• 제21권11호
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• pp.623-627
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• 2011

This is a study on the distribution of acoustic emission parameters during a burst test for a type-II CNG vehicle fuel tank. A resonant AE sensor with a central frequency of 150 kHz was attached to the composite materials in the center of the fuel tank. The pressure was increased from 30 to 100% of the expected burst pressure and was maintained for 10 minutes at each level. Damage at 70% of expected burst pressure occurred by various damage mechanisms including fiber breakage and delamination, while that of below 60% only occurred by matrix crack initiation and growth. The count, duration and rise time of the AE signal at 60% of the expected burst pressure are distributed below 500, 5000 ${\mu}s$ and 300 ${\mu}s$, respectively. Then, at above 70% they increased with pressure by superimposing of individual AE signal generated at a nearby place. These results confirmed that the analysis of the distribution of AE parameters is an effective tool for estimating damage of a CNG fuel tank.

• 한국정밀공학회지
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• 제26권11호
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• pp.12-19
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• 2009

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.371-376
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• 1994

This paper presents an on-line modeling method approach for the machine condition. the machine condition is continuously monitored with a sensor such as, a vibration, a current, an acoustic emission (AE) sensor. In this study, neural network modeling by radial basis function is designed for analysis a prediction error. An on-line learning algorithm is designed using the RLS(recursive least square) estimation and the existing clustering method of Kohonen neural network. Experimental results show that the proposed RBNN modeling is suitable for predicting simulated data.

• 한국정밀공학회지
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• 제31권11호
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• pp.1041-1050
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• 2014

A design and analysis for new foot sensor that measures pressure distribution while walking or running in daily life is introduced. In the process of the sensor design, the shape, mechanism composing of the sensor, and variables that dominate sensor's sensitivity are investigated. Through these variables analysis, an optimal shape and dimension were determined. The effects of variables on sensor's sensitivity and the relationship between each variable are proved by analyses and experiments.

• 터널과지하공간
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• 제25권1호
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• pp.56-67
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• 2015

본 논문에서는 횡등방성 매질에 적용 가능한 음원추적기법을 제안하고 이를 실험적으로 검증하였다. 분할근사법을 바탕으로 매질의 속도 이방성을 고려하였으며 이 방법은 단순한 계산을 통하여 음원추적을 가능하게 한다. AE 측정 결과로부터 P파 도달시간을 결정할 때 Two-step AIC 알고리즘을 적용하였고 이 실험결과와 분할된 요소를 비교하여 최소 오차 요소를 음원의 위치로 결정하였다. 개발된 알고리즘의 적용성을 검증하기 위하여 시멘트 모르타르를 이용한 인공 횡등방성 시험편을 제작하고 연필심 압절을 음원으로 하는 일련의 시험을 수행하였다. 연필심 압절 위치와 음원추적 결과 간의 거리를 절대오차로 정의할 때, 1.60 mm ~ 14.46 mm의 오차범위와 8.57 mm의 평균오차가 측정되었고 이는 시험편과 AE 센서의 크기를 고려할 때 수용할 만한 수준인 것으로 판단되었다. 또한, 서로 다른 검출한계 수준에 따른 음원추적 결과를 비교했을 때 비슷한 수준의 오차가 측정되어 본 기법은 실험 시 배경잡음의 영향을 적게 받는 것으로 판단된다. 측정된 절대오차를 각 축방향 오차로 분해하여 AE 센서 부착위치의 영향을 파악할 수 있었으며 센서의 최적 위치를 결정하면 더 정밀한 음원추적 결과를 얻을 수 있을 것으로 판단된다.

• 한국지반공학회논문집
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• 제27권1호
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• pp.25-34
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• 2011

비탈면의 계측은 현장 접근성이 떨어지고 장기적인 계측이 어려워 이론적이거나 경험에 의존하는 것이 일반적이기 때문에 재난, 재해에 대한 조짐을 예측하기란 매우 어려운 실정이다. 따라서 본 논문에서는 비탈면의 붕괴를 예측하는 효과적인 방법과 현장 적용성에 대한 내용을 실험적 연구를 실시한 내용을 다루었다. 비탈면의 붕괴를 예측하는 방법은 재료의 파괴시 발생되는 음파를 WEAD라 불리는 AE센서를 이용하여 지반분야에 적용함으로써 비탈면의 붕괴를 예측 할 수 있었다. 비탈면 붕괴시 발생되는 AE파라미터는 전단 실험과 휨 실험을 실시하여 확보하였고 이를 토대로 파괴기준을 마련하였다. 시험시공은 비탈면 붕괴이력이 있고 붕괴가능성이 존재하는 비탈면에 적용해 보았고 실험결과 AE파라미터는 파괴기준에 넘지 않아 안정한 것으로 나타났으며 실제 비탈면의 붕괴 증후는 없는 것으로 나타나 적용성이 우수한 것으로 분석되었다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.921-924
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• 2004

This paper is to investigate a crack for plasma sprayed MCrAlY coated material by acoustic emission method in 4-point bending test. The CoNiCrAlY is coated on Inconel-718 by vacuum plasma spray process. Micro-hardness measurement was conducted by means of Micro Vickers-hardness indentor. The porosity of coating layer was measured using a SEM and Image Analyzer. AE monitoring system is composed of PICO type sensor, a wide band preamplifier(40dB), a PC and AE DSP(16/32 PAC) board. The AE count, Hit and energy of coating specimens is measured according to coating thickness.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 춘계학술대회 논문집
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• pp.300-304
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• 1993

Chip formation control is an important problem in the automation of manufacturing process, since the continuous chip can cause catastrophic failures of the tooling and entangle the workpiece causing damage. However, it is impossible to predict chip form correctly due to the complex nature of cutting process. In order to detect the chip form for unmanned manufacturing, a new identification method is proposed. The feasibility of using acoustic emission signals from the sensing plate for identification of chip form is investigated. Experiments were conducted under the various cutting conditions. When the acoustic emission sensor is attached to the sensing plate, it turns out that the moving averaged AE signals correlated well with the collision of segmented chips with the plate. The sensitivity of moving averaged AE signals to chip congestions due to continuous chip formation is illustrated as well.

• 한국기계가공학회지
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• 제11권2호
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• pp.34-39
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• 2012

In this study, the friction welding experiment was performed by using the design of experiment. And the signal data acquired by acoustic emission sensor were analyzed to predict the tensile strength of friction welding part at friction welding process for AZ31 magnesium alloy. A dimensionless coefficient($\phi_{AE}$), which consisted in the square of AE rms and variance, was defined as the characteristic of friction welding and the prediction equation was obtained by using linear regression. As the result of analysis, it was seen that the correlation between predicted and measured values became very close and on-line prediction of the ensile strength was possible in friction welding part.

• 한국정밀공학회지
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• 제26권9호
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• pp.53-57
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• 2009

There are technical requirements to manufacture large size functional parts with not only simple geometries like a flat or spherical surface but also sculptured geometries. In addition, the required machining accuracy for these parts is becoming more severe. In general, the form accuracy of machined parts is determined by the relative position between workpiece and tool during machining process. To improve machining accuracy the relative position errors should be maintained within the required accuracy. This study deals with the estimation and calibration of depth of cut using the AE signal in micro-machining. Also, this sensing technique can be applied to detect the initial contact between workpiece and tool.