• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.79-91
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• 2006

A new methodology of guided wave based nondestructive testing (NDT) is developed to detect crack damage in civil infrastructures such as steel bridges without using prior baseline data. In conventional guided wave based techniques, damage is often identified by comparing the "current" data obtained from a potentially damaged condition of a structure with the "past" baseline data collected at the pristine condition of the structure. However, it has been reported that this type of pattern comparison with the baseline data can lead to increased false alarms due to its susceptibility to varying operational and environmental conditions of the structure. To develop a more robust damage diagnosis technique, a new concept of NDT is conceived so that cracks can be detected without direct comparison with previously obtained baseline data. The proposed NDT technique utilizes the polarization characteristics of the piezoelectric wafers attached on the both sides of the thin metal structure. Crack formation creates Lamb wave mode conversion due to a sudden change in the thickness of the structure. Then, the proposed technique instantly detects the appearance of the crack by extracting this mode conversion from the measured Lamb waves even at the presence of changing operational and environmental conditions. Numerical and experimental results are presented to demonstrate the applicability of the proposed technique to crack detection.

• Polymer(Korea)
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• v.28 no.4
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• pp.285-290
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• 2004

Nondestructive damage sensitivity of carbon nanotube(CNT) and nanofiber (CNF)/epoxy composites with their adding contents was investigated using electro-micromechanical technique. Carbon black (CB) was used only for the comparison with CNT and CNF. The fracture of carbon fiber was detected by acoustic emission (AE), which was correlated to the change in electrical resistance, ΔR under double-matrix composites (DMC) test. Stress sensing on carbon nanocomposites was performed by electro-pullout test under uniform cyclic loading. At the same volume fraction, the damage sensitivity for fiber fracture, matrix deformation and stress sensing were highest for CNT/epoxy composite, whereas for CB/epoxy composite they were the lowest among three carbon nanomaterials (CNMs). Damage sensitivity was correlated with morphological observation of carbon nanocomposites. Homogeneous dispersion among CNMs could be keying parameters for better damage monitoring. In this study, damage sensing of carbon nanocomposites could be evaluated well nondestructively by the electrical resistance measurement with AE.

• Composites Research
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• v.27 no.6
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• pp.219-224
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• 2014

Nancomposites manufacture has been developed rapidly, because of reinforcing effects of CNT in terms of mechanical, electrical and thermal properties. In this study, 10 wt% CNT paste was fabricated with good dispersion state and easy processability. Damage sensing and reinforcing effect of CNT paste were investigated in nanocomposites. 10 wt% CNT paste exhibited better tensile and flexural properties than those of general 1 wt% CNT nanocomposites. To observe the healing effect of CNT paste, a crack was made artificially with 30wt% CF30wt%/PP composites, and the CNT paste was filled inside the crack. The damage sensing of CNT paste in CF30wt%/PP composites was investigated by electrical resistance measurement and mechanical tests. CNT paste exhibited good reinforcing effect in mechanical properties of CF30wt%/PP composites, and this reinforcing effect was getting better with larger cracks. The reason was because CNT paste had good interfacial adhesion with CF30wt%/PP composites to resist crack propagation. In electrical resistance measurement, there was a jump in electrical resistance signal at the adhesion interface. The jumping signal could be used to predict fracture of CF/PP composites. CNT nanocomposites for damage sensing had crack reducing effect and damage detection using electrical resistance method.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.405-406
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• 2022

재난 시 피해자를 위해 사용되는 고압산소치료 시 흔한 부작용으로 높아진 압력에 적응하지 못하고 귀의 통증을 비롯한 압력 손상의 증상이 발현되는 경우가 종종 존재하여 이는 고압산소치료 시 해결해야 할 과제로 떠올랐다. 이에 본 본 연구에서는 고압산소치료기에 개발된 압력손상방지장치를 연결하여 적용하였을 때 고압산소치료 중 압력손상이 조기 감지되고 이를 통해 고압산소치료를 받는 피해자가 압력손상이 진행되지 않는지에 대하여 연구하였다. 압력손상방지장치를 활용하면 고압산소치료 중 압력손상이 조기 감지되고 이를 통해 고압산소치료를 받는 피해자가 압력손상이 심하게 진행되지 않는데 도움을 받을 수 있다. 단 이는 피해자 본인이 체내압력 조절이 가능한 상태여야 하며 의식이 없거나 협조가 어려운 대상에 대한 압력손상방지는 또 다른 도전으로 향후 이에 대한 추가적 연구가 필요하다.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.129-129
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• 2011

ISFET (ion sensitive field effect transistor)는 용액 중의 각종 이온 농도를 측정하는 반도체 이온 센서이다. ISFET는 작은 소자 크기, 견고한 구조, 즉각적인 반응속도, 기존의 CMOS공정과 호환이 가능하다는 장점이 있다. ISFET의 기본 구조는 기존의 MOSFET (metal oxide semiconductor field effect transistor)에서 고안되었으며, ISFET는 기존의 MOSFET의 게이트 전극 부분이 기준전극과 전해질로 대체되어진 구조를 가지고 있다. ISFET소자의 pH 감지 메커니즘은 감지막의 표면에서 pH용액 속의 이온들이 감지막의 표면에서 속박되어 막의 표면전위의 변화를 유발하는 것을 이용한다. 그 결과, ISFET의 문턱전압의 변화를 일으키게 되고 드레인 전류의 양 또한 달라지게 된다. ISFET의 높은 pH감지능력을 얻기 위하여 높은 high-k물질 들이 감지막으로서 연구되었다. Al2O3와 HfO2는 높은 유전상수, non-ideal 효과에 대한 immunity 그리고 높은 pH 감지능력 등 많은 장점을 가지고 있는 물질로 알려졌다. 본 연구에서는, SiO2/HfO2/Al2O3 (OHA) 적층막을 이용한 EIS (electrolyte- insulator-silicon) pH센서를 제작하였다. EIS구조는 ISFET로의 적용이 용이하며 ISFET보다 제작 방법과 소자 구조가 간단하다는 장점이 있다. HfO2은 22~25의 높은 유전상수를 가지며 높은 pH 감지능력으로 인하여 감지막으로서 많은 연구가 이루어지고 있는 물질이다. 하지만 HfO2의 물질이 가진 고유의 특성상 화학적 용액에 대한 non-ideal 효과는 다른 금속계열 산화막에 비하여 취약한 모습을 보인다. 반면에 Al2O3의 유전상수는 HfO2보다 작지만 화학용액으로 인한 손상에 대하여 강한 immunity가 있는 재료이다. 이러한 물질들의 성질을 고려하여 OHA의 새로운 감지막의 적층구조를 생각하였다. 먼저 Si과 high-k물질의 양호한 계면상태를 이루기 위하여 5 nm의 얇은 SiO2막을 완충막으로서 성장시켰다. 다음으로 높은 유전상수를 가지고 있는 8 nm의 HfO2을 증착시킴으로서 소자의 물리적 손상에 대한 안정성을 향상시켰다. 최종적으로 화학용액과 직접적인 접촉이 되는 부분은 non-ideal 효과에 강한 Al2O3을 적층하여 소자의 화학적 손상에 문제점을 개선시켰다. 결론적으로 감지막의 적층 모델링을 통하여 각각의 high-k 물질이 가진 고유의 특성에 대한 한계점을 극복함으로써 높은 pH 감지능력뿐만 아니라 신뢰성 있는 pH 센서가 제작 되었다.

• Composites Research
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• v.26 no.1
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• pp.1-6
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• 2013

CNT-polypropylene (PP) composites were compounded by solvent dispersion method with uniform dispersion by using twin screw extruder. Damage sensing effects based on conductive carbon nanotubes (CNT) were evaluated to monitor the internal damage of CNT-PP composites using electrical resistance measurement. Mechanical and interfacial properties of CNT-PP composites were investigated and compared with neat PP. The mechanical properties of PP matrix were improved after adding CNT, because of the reinforcing effect of CNT fillers. In order to monitor the internal damage of CNT-PP composite, the change in electrical resistance of the composites was measured under fatigue loading and bending tests. CNT fillers exhibited good sensing under electrical resistance measurements. It is shown that CNT-PP composites with low CNT contents allow identifying critical cyclic loading, which are found to be accompanied with the internal failure.

• Composites Research
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• v.18 no.6
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• pp.26-33
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• 2005

The mechanical properties of composite materials may severely degrade in the presence of damage. Especially, the high-velocity impact such as bird strike, a hailstorm, and a small piece of tire or stone during high taxing, can cause considerable damage to the structures and sub-system in spite of a very small mass. However, it is not easy to detect the damage in composite plates using a single technique or any conventional methods. In this paper, the PVDF(polyvinylidene fluoride) film sensors were used for monitoring high-velocity impact damage initiation and propagation in composite laminates. The WT(wavelet transform) and STFT(short time Fourier transform) are used to decompose the sensor signals. A ultrasonic C-scan and a digital microscope are also used to examine the extent of the damage in each case. This research shows how various sensing techniques, PVDF sensor in particular, can be used to characterize high-velocity impact damage in advanced composite.

• Composites Research
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• v.17 no.4
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• pp.61-67
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• 2004

Nondestructive damage sensitivity on single-basalt fiber/epoxy composites was evaluated by micromechanical technique and acoustic emission (AE). Piezoelectric lead-zirconate-titanate (PZT), polyvinylidene fluoride (PVDF) and poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) copolymer were used as AE sensor, respectively. In single-fiber composite, the damage sensing with different sensor types were compared to each other. Piezoelectric PVDF polymer sensor was embedded in and attached on the composite, whereas PZT sensor was only attached on the surface of specimen. In case of embedded polymer sensors, responding sensitivity was higher than that of the attached case. It can be due to full constraint inside specimen to transfer elastic wave coming from micro-deformation. For both the attached and the embedded cases, the sensitivity of P(VDF-TrFE) sensor was almost same as that of conventional PVDF sensor.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.370-375
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• 2003

Optical fiber vibrations sensors (OFVSs) and extrinsic Fabry-Perot interferometer (EFPI) were used in damage monitoring of fiber-metal laminates(FML). The optical fiber vibration sensor and EFPI were applied in order to detect and evaluate the strain, damage and failure of FML. Damages in composites, such as matrix cracks, delamination and fiber breakage may occur as a result of excessive load, fatigue and low-velocity impacts. Tensile and indentation test was performed with the measurement of optical signal and acoustic emission (AE). The signals of the optical fiber vibration sensor due to damages were quantitatively evaluated by wavelet transform. It was found that damage information of comparable in quality to acoustic emission data could be obtained from the optical fiber vibration sensor signals.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.4
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• pp.511-523
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• 2023

Research on the integration of unmanned aerial vehicles and deep learning for reinforced concrete damage detection is actively underway. Convolutional neural networks have a high impact on the performance of image classification, detection, and segmentation as backbones. The MobileNet, a pre-trained convolutional neural network, is efficient as a backbone for an unmanned aerial vehicle-based damage detection model because it can achieve sufficient accuracy with low computational complexity. Analyzing vanilla convolutional neural networks and MobileNet under various conditions, MobileNet was evaluated to have a verification accuracy 6.0~9.0% higher than vanilla convolutional neural networks with 15.9~22.9% lower computational complexity. MobileNetV2, MobileNetV3Large and MobileNetV3Small showed almost identical maximum verification accuracy, and the optimal conditions for MobileNet's reinforced concrete damage image feature extraction were analyzed to be the optimizer RMSprop, no dropout, and average pooling. The maximum validation accuracy of 75.49% for 7 types of damage detection based on MobilenetV2 derived in this study can be improved by image accumulation and continuous learning.