• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.5
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• pp.657-673
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• 2019

A monitoring method based on acoustic emission (AE) sensor has been widely used to evaluate the damage of structures in underground rock. The acoustic emission signal generated from cracking in material is analyzed as various acoustic emission parameters in time and frequency domain. To investigate from initial crack generation to final failure of rock material, it is important to understand the characteristics of acoustic emission parameters according to the stress ratio and rock strength. In this study, uniaxial compression tests were performed using very strong and weak rock specimen in order to investigate the acoustic emission parameters when the failure of specimen occurred. In the results of experimental tests, the event, root-mean-square (RMS) voltage, amplitude, and absolute energy of very strong rock specimen were larger than those of the weak rock specimen with an increase of stress ratio. In addition, the acoustic emission parameters related in frequency were more affected by specification (e.g., operation and resonant frequency) of sensors than the stress ratio or rock strength. It is expected that this study may be meaningful for evaluating the damage of underground rock when the health monitoring based on the acoustic emission technique will be performed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.7-10
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• 2023

최근 기후 변화가 심각해짐에 따라 수소 에너지에 대한 관심이 집중되고 있으며 이를 안전하게 운송/보관할 수 있는 용기에 대한 연구도 활발히 진행되고 있다. 특히 고압 가스를 저장하는 TypeIII 용기의 노후화 및 안전과 관련되어 결함을 인지하는 연구가 활발하다. 그러나 이 용기의 외각층을 이루는 CFRP 소재는 탄소 섬유와 에폭시가 복잡한 구조로 구성되어 결함별 탐지가 매우 어렵다. 본 논문에서는 음향방출시험과 딥러닝을 활용하여 CFRP 결함 데이터셋을 구축하고 이를 분류할 수 있는 모델을 제안한다. 특히 CFRP 시편을 직접 제작하여 AE 센서를 부착하고 파괴하여 파형 데이터를 수집하였다. 이후 표현 학습을 통해 데이터의 특징을 압축/추출하고 유사도를 비교해 결함별 데이터를 판별하는 알고리즘을 개발하였다. 구축된 데이터셋의 실루엣 계수는 0.86으로 높은 군집도를 보였다. 마지막으로 구축된 데이터셋을 실시간으로 분류할 수 있는 1D-CNN 딥러닝 모델을 개발하였으며 99.33%의 높은 분류 정확도를 보였다.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.227-236
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• 2003

Leaks in underground pipelines can cause social, environmental and economical problems. One of relevant countermeasures against leaks is to find and repair of leak points of the pipes. Leak noise is a good source to identify the location of leak points of the pipelines. Although there have been several methods to detect the leak location with leak noise, such as listening rods, hydrophones or ground microphones, they have not been so efficient tools. In this paper, acoustic emission (AE) sensors and accelermeters are used to detect leak locations which could provide all easier and move efficient method. Filtering, signal processing and algorithm of raw input data from sensors for the detection of leak location are described. A 120m-long pipeline system for experiment is installed and the results with the system show that the algorithm with the AE sensors and accelerometers offers accurate pinpointing of leaks. Theoretical analysis of sound wave propagation speed of water in underground pipes, which is critically important in leak locating, is also described.

• Composites Research
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• v.36 no.6
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• pp.429-434
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• 2023

In this study, aimed at improving the existing acoustic emission sensor for real time monitoring, a macro-fiber composite (MFC) transducer was employed as the acoustic emission sensor in the gas leak detection system. Prior to implementation, structural analysis was conducted to optimize the MFC's design. Consequently, the flexibility of the MFC facilitated excellent adherence to curved pipes, enabling the reception of acoustic emission (AE) signals without complications. Analysis of AE signals revealed substantial variations in parameter values for both high-pressure and low-pressure leaks. Notably, in the parameters of the Fast Fourier Transform (FFT) graph, the change amounted to 120% to 626% for high-pressure leaks compared to the case without leaks, and approximately 9% to 22% for low-pressure leaks. Furthermore, depending on the distance from the leak site, the magnitude of change in parameters tended to decrease as the distance increased. As the results, in the future, not only will it be possible to detect a leak by detecting the amount of parameter change in the future, but it will also be possible to identify the location of the leak from the amount of change.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.7
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• pp.891-897
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• 2013

In this study, the compressive deformation behaviors of aluminum alloy under high strain rates were investigated by means of a SHPB test. An acoustic emission (AE) technique was also employed to monitor the signals detected from the deformation during the entire impact by using an AE sensor connected to the specimen with a waveguide in real time. AE signals were analyzed in terms of AE amplitude, AE energy and peak frequency. The impacted specimen surface and side area were observed after the test to identify the particular features in the AE signal corresponding to the specific types of damage mechanisms. As the strain increased, the AE amplitude and AE energy increased whereas the AE peak frequency decreased. It was elucidated that each AE signal was closely associated with the specific damage mechanism in the material.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.3
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• pp.281-287
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• 2001

For the conventional two-dimensional source location of acoustic emission (AE) based on the threshold crossing, wave velocity has to be measured in the actual structure to calculate the arrival-time difference and thus to form the two hyperbolae. Velocity is dependent on the fiber orientation, however, due to the dependence of elastic modulus on fiber orientation in anisotropic materials such as compost#e plates. This tan affect the accuracy of AE source location and make the source location procedure complicated. In this study, we propose a method to reduce the location error in anisotropic plates by using the numerical solution of nonlinear equations, where the velocity term has been removed by employing the fourth sensor. The efficiency and validity of the proposed method has also been experimentally verified.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.135-136
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• 2012

• Proceedings of the Optical Society of Korea Conference
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• 2007.02a
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• pp.239-240
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• 2007

• 한국가스학회:학술대회논문집
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• 1999.09a
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• pp.127-132
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• 1999

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.678-679
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• 2013