• 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.

• 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.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.67-74
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• 2023

A large number of concrete structures are built and used around the world. To ensure their safe and continuous use, these structures require constant inspection and maintenance. While man-powered inspection and maintenance techniques are efficient, they can only provide intermittent status checks at the time of on-site inspection. Therefore, there is a growing need for a system that can continuously monitor the condition of the structure. A study was conducted to detect cracks and damage by installing a conductive coating on the surface of a concrete structure. A parallel resistance pattern that can monitor the occurrence and progression of cracks was developed by reflecting the structural characteristics of concrete structure. An empirical study was conducted to veryfy the application of the proposed method. The crack detection pattern was installed on the reinforced concrete beams, and the crack monitoring method was verified through applying a load on the beams.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.36-44
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• 2024

This paper presents the application of Convolutional Neural Networks (CNNs) and Region of Interest (ROI) techniques for concrete crack analysis. Surfaces of concrete structures, such as beams, etc., are exposed to fatigue stress and cyclic loads, typically resulting in the initiation of cracks at a microscopic level on the structure's surface. Early detection enables preventative measures to mitigate potential damage and failures. Conventional manual inspections often yield subpar results, especially for large-scale infrastructure where access is challenging and detecting cracks can be difficult. This paper presents data collection, edge segmentation and ROI techniques application, and analysis of concrete cracks using Convolutional Neural Networks. This paper aims to achieve the following objectives: Firstly, achieving improved accuracy in crack detection using image-based technology compared to traditional manual inspection methods. Secondly, developing an algorithm that utilizes enhanced Sobel edge segmentation and ROI techniques. The algorithm provides automated crack detection capabilities for non-destructive testing.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.94-94
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• 2011

배관 구조물에서는 내부 미세 균열에서부터 국부 좌굴, 볼트 풀림, 피로 균열 등과 같이 다양한 형태의 손상이 복합적으로 발생 가능하다. 이러한 복합 손상은 배관 구조물의 누수, 누유 등의 사고를 야기할 수 있다. 하지만 기존의 단일 스케일 계측 시스템으로부터 복합 손상에 의한 실시간 누수를 진단하기는 매우 어렵다. 본 연구 단계에서는 누수를 야기하는 복합 손상을 효율적으로 진단하기 위하여 선행 연구에서 제안된 압전센서를 이용한 자가 계측 회로 기반의 다중 스케일 계측 시스템을 구조물의 복합 손상 진단에 적용하였다. 자가 계측 회로 기반 다중 스케일 계측 시스템은 크게 두 가지 형태의 신호를 계측한다. 첫 번째 스케일은 임피던스 계측으로부터 특정 주파수 대역폭에 대한 구조 응답을 계측하며, 두 번째 스케일은 유도 초음파 계측으로부터 단일 중심 주파수에 해당하는 구조물의 응답을 계측한다. 복합 손상을 손상 유형별로 분류하기 위하여 E/M 임피던스(Electro-mechanical impedance)및 유도 초음파(Guided wave) 계측으로부터 추출한 특성을 이용하여 2차원 손상지수를 계산하고 이를 지도학습 기반 패턴인식 기법(Supervised learning based pattern recognition) 중 확률론적 신경망 기법(Probabilistic Neural Network, PNN)에 적용한다. 제안된 기법의 적용성 검토를 위하여 파이프 구조물에 인위적으로 다중 손상을 생성시켜 시험을 수행하였다. 본 연구에서 제안된 기법이 실제 배관 구조물에 성공적으로 적용된다면 손상 부재의 거동 및 구조물 성능의 손상에 대한 영향을 효율적으로 진단하고 평가함으로써 배관 구조물의 효과적인 유지관리가 가능할 것으로 예상된다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.1
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• pp.43-58
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• 2002

A methodology to nondestructively locate and estimate size of damage in beam-type structures using a few natural frequencies or a few mode shapes is presented. A damage-localization algorithm to locate damage from changes in natural frequencies and a damage-sizing algorithm to estimate crack-size from natural frequency perturbation are outlined. A damage index algorithm to localize and estimate severity of damage from monitoring changes in mode shapes is outlined. The frequency-based method and the mode-shape-based method are evaluated for several damage scenarios by locating and sizing damage in PS concrete beams lot which a few natural frequencies and mode shapes are generated from finite element models. The result of the analyses indicates that the two methods correctly localize and closely estimate the size of the crack simulated in the test beam.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.347-348
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• 2022

본 연구에서는 무인이동체를 활용한 철도교량의 외관조사 점검을 보다 효율적이고 객관성 있게 수행하기 위하여 무인이동체를 통해 촬영된 이미지를 딥러닝 기반 분석기술을 활용하여 손상 자동으로 분석 하기위한 기술을 연구하였다. 철도교량의 외관 손상 중 균열, 콘크리트 박리·박락, 누수, 철근노출에 대한 손상 이미지를 추출하여 딥러닝 분석 모델을 생성하고 학습한 분석 모델을 적용한 시스템을 실제 현장에 적용 테스트를 수행하였으며 학습 구현된 분석모델의 검측 재현율을 검토한 결과 평균 95%이상의 감지성능을 검토할 수 있었다. 개발 제안된 자동손상분석 기술은 기존 육안점검 결과 대비 보다 객관적이고 정밀한 손상 검측이 가능하며 철도 유지관리 분야에서 무인이동체를 활용한 외관조사 업무를 수행함에 있어 기존 대비 객관적인 결과도출과 소요시간, 비용저감이 가능할 것으로 기대된다.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.32-38
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• 2001

Although the ultrasonic method has been developed and used widely in the fields, it has been used only for measuring the defect size and thickness loss. In this study, the relationship between surface wave attenuation through micro-crack growth and variation of velocity under repeated cyclic loading has been investigated. The specimens are adopted from 2.25Cr-1Mo steel, which is used for power plant and pipeline system, and have dimensions of $200{\times}40{\times}4mm$. The results of ultrasonic test with a 5MHz transducer show that surface wave velocity gradually decreases from the point of 60% of fatigue life and the crack length of 2mm with the increasing fatigue cycles. From the results of this study, it is found that the technique using the ultrasonic velocity change is one of very useful methods to evaluate the fatigue life nondestructively.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.827-829
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• 2021

현대사회의 시설물 중 다수가 콘크리트를 사용하여 건설되었고, 재료적 성질로 인해 균열, 박락, 백태 등의 손상이 발생하고 있고 시설물 관리가 요구되고 있다. 하지만, 현재 시설물 관리는 사람의 육안 점검을 정기적으로 수행하고 있으나, 높은 시설물이나 맨눈으로 확인할 수 없는 시설물의 경우 관리가 어렵다. 이에 본 논문에서는 다양한 영상장비를 활용해 시설물의 이미지에서 균열을 분류하는 알고리즘을 제안한다. 균열 분류 알고리즘은 산업 이상 감지 데이터 세트인 MVTec AD 데이터 세트를 사전 학습하고 L2 auto-encoder를 사용하여 균열을 분류한다. MVTec AD 데이터 세트를 사전학습시킴으로써 균열, 박락, 백태 등의 특징을 학습시킬 수 있을 것으로 기대한다.

• Composites Research
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• v.15 no.2
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• pp.11-17
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• 2002

The piezoelectric thin film sensor can be used to interpret variations in structural and material properties, e.g. for structural integrity monitoring and assessment. To illustrate one of this potential benefit, PVDF (polyvinylidene fluoride) film sensors are used for monitoring impact damage in Gr/Ep composite panels. Both PVDF film sensors and strain gages are attached to the surface of Gr/Ep specimens. A series of impact tests at various impact energy by changing impact mass the height are performed on the instrumented drop weight impact tester. The sensor responses are carefully examined to predict the onset of impact damage such as indentation, matrix cracking, and delamination, etc. Test results show that the particular waveforms of sensor signals implying the damage initiation and development are detected above the damage initiation impact energy. As expected, the PVDF film sensor is found to be more sensitive to impact damage initiation event than the strain gage.