• Korean Journal of Materials Research
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• v.8 no.6
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• pp.565-570
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• 1998

SiCp/6061AI 복합재료의 파괴인성을 평가하기 위하여 정적파괴인성에 대해서는 복수시험편법을, 동적파괴인성시험에 대해서는 stop block법을 실시하였다. 주균열은 예비균열의 선단에서 시험편두께방향 전역에 걸쳐서 일시에 발생하는 것이 아니고, 균열발생의 초기단계에서 국부적으로 형성된 균열이 시험편두께방향으로의 균열의 확장을 완료한 후 주균열로 이행해 간다. 정적 및 동적시험에서 컴플라이언스변화율법에 의해 검출된 균열발생점은 균열확장의 완료점과 거의 일치하고 있기 때문에 본 재료의 파괴인성 결정에 유효하다. 본 재료에서 동적파괴인성치는 정적파괴인성치보다 크게 나타났다. 이것은 동적충격시 입자파괴에 의한 에너지의 흡수.분산효과와 균열진전경로의 큰 편향에 기인한다고 생각된다.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.493-500
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• 2009

An ultrasonic signal processing algorithm was developed for extracting the information of cracks generated around the keyway of a turbine rotor disk. B-scan images were obtained by using keyway specimens and an ultrasonic scan system with x-y position controller. The B-scan images were used as input images for 2-Dimensional signal processing, and the algorithm was constructed with four processing stages of pre-processing, crack candidate region detection, crack region classification and crack information extraction. It is confirmed by experiments that the developed algorithm is effective for the quantitative evaluation of cracks generated around the keyway of turbine rotor disk.

• Proceedings of the KWS Conference
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• 2001.05a
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• pp.318-321
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• 2001

클래딩은 주요 산업분야에 내마모성, 내부식성의 향상을 위해 사용되고 있다. 그러나 클래딩 공정에서는 모재와 클래딩 재료의 물리적, 화학적 특성의 차이와 여러 가지 공정 변수의 영향으로 제품의 사용에 치명적인 손상을 줄 수 있는 균열, 슬래그 개재물, 기공등의 불연속이 발생하기 쉽다. 본 연구에서는 클래딩 시에 발생되는 불연속을 실시간으로 검출하는데 아주 우수한 검출능력을 갖고 있는 비파괴 검사 방법인 음향방출시험을 적용하고 검출된 신호에 대한 주파수 분석과 2차원 위치표정을 실시하여 균열, 기공 등의 불연속을 검출하였고 이를 주사전자현미경을 통하여 확인하였다. 음향방출법에 의해 클래딩부에서 발생하는 결함에 대한 실시간 평가가 가능함을 입증하였으며, 특히 다층 클래딩이나 넓은 면적의 클래딩시에 불연속을 가장 신속하게 감지할 수 있으므로 이를 생산공정에 활용한다면 클래딩 또는 용접부 품질감시를 위한 효과적인 방법이 될 것이다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.6
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• pp.573-577
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• 2009

When ultrasound propagates to a crack, transmitted and reflected waves are generated. These waves have useful information for the detection of the crack lying in a structure. In this paper, using finite element analysis, displacements round a inclined crack were obtained for 4 different inclination angles. Fourier transformation is applied to the results to research the frequency characteristics depending on the various locations around the crack. 2-dimensional plane stress model is considered, and finite element software ABAQUS/Explicit is used.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.2
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• pp.197-203
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• 2001

Micro-defects induced by design and production failure or working environments are known as the cause of SCC(Stress Corrosion Cracking) in aged structures. Therefore, the evaluation of structural integrity based on micro-cracks is required not only a manufacturing step but also in-service term. So we introduce a new nondestructive inspection method using the magneto-optical film to detect micro-cracks. The method has some advantage such as high testing speed, real time data acquistion and the possibility of remote sensing by using of a magneto-optical film that takes advantage of the change of magnetic domains and domain walls. This paper introduces the concept of the new nondestructive inspection method using the magneto-optical film, also proves the possibility of this method as a remote testing system under oscillating load considering application on real fields by applying the method to four types of specimens.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.479-484
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• 2009

Nondestructive evaluation(NDE) of ceramic matrix composites is essential for developing reliable ceramics for industrial applications. In the work, C-Scan image analysis has been used to characterize surface crack of SiC ceramics nondestructively. The possibility of detection of surface crack were carried out experimentally by two types of ultrasonic equipment of SDS-win and $\mu$-SDS, and three types of transducer of 25, 50 and 125 MHz. A surface micro-crack of ceramics was not detected by transducer of 25 MHz and 50 MHz. Though the focus method was detected dimly the crack by transducer of 125 MHz, the defocus method could detect the shape of diamond indenter. As a whole, the focus method and the defocus method came to the conclusion that micro crack have a good possibility for detection.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.161-168
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• 2021

Cracks affect the robustness of infrastructures such as buildings, bridge, pavement, and pipelines. This paper presents an automated crack detection system which detect cracks in diverse surfaces. We first constructed the combined crack dataset, consists of multiple crack datasets in diverse domains presented in prior studies. Then, state-of-the-art deep learning models in computer vision tasks including VGG, ResNet, WideResNet, ResNeXt, DenseNet, and EfficientNet, were used to validate the performance of crack detection. We divided the combined dataset into train (80%) and test set (20%) to evaluate the employed models. DenseNet121 showed the highest accuracy at 96.20% with relatively low number of parameters compared to other models. Based on the validation procedures of the advanced deep learning models in crack detection task, we shed light on the cost-effective automated crack detection system which can be applied to different surfaces and structures with low computing resources.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.377-380
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• 2023

본 논문에서는 합성곱 신경망(Convolutional Neural Networks, CNN)과 탄성왜곡(Elastic Distortion) 기법을 통한 데이터 증강 기법을 활용하여 학습 데이터를 구축하는 프레임워크를 제안한다. 실제 균열 이미지는 정형화된 형태가 없고 복잡한 패턴을 지니고 있어 구하기 어려울 뿐만 아니라, 데이터를 확보할 때 위험한 상황에 노출될 우려가 있다. 이러한 데이터베이스 구축 문제점을 본 논문에서 제안하는 데이터 증강 기법을 통해 비용적, 시간적 측면에서 효율적으로 해결한다. 세부적으로는 DeepCrack의 데이터를 10배 이상 증가하여 실제 균열의 특징을 반영한 메타 데이터를 생성하여 U-net을 학습하였다. 성능을 검증하기 위해 균열 탐지 연구를 진행한 결과, IoU 정확도가 향상되었음을 확인하였다. 데이터를 증강하지 않았을 경우 잘못 예측(FP)된 경우의 비율이 약 25%였으나, 데이터 증강을 통해 3%까지 감소하였음을 확인하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.599-608
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• 2017

Cracks on the asphalt road surface can affect the speed of the car, the consumption of fuel, the ride quality of the road, and the durability of the road surface. Such cracks in roads can lead to very dangerous consequences for long periods of time. To prevent such risks, it is necessary to identify cracks and take appropriate action. It takes too much time and money to do it. Also, it is difficult to use expensive laser equipment vehicles for initial cost and equipment operation. In this paper, we propose an effective detection method of road surface defect using ROI (Region of Interest) setting and cany edge detection method using UAV image. The results of this study can be presented as efficient method for road surface flaw detection and maintenance using UAV. In addition, it can be used to detect cracks such as various buildings and civil engineering structures such as buildings, outer walls, large-scale storage tanks other than roads, and cost reduction effect can be expected.

• Journal of the Korean Geosynthetics Society
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• v.21 no.2
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• pp.11-19
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• 2022

In this paper, we propose a GoogleNet transfer learning and CNN-LSTM combination method to improve the time-series prediction performance for crack detection using crack data captured inside the sewer pipes. LSTM can solve the long-term dependency problem of CNN, so spatial and temporal characteristics can be considered at the same time. The predictive performance of the proposed method is excellent in all test variables as a result of comparing the RMSE(Root Mean Square Error) for time series sections using the crack data inside the sewer pipe. In addition, as a result of examining the prediction performance at the time of data generation, the proposed method was verified that it is effective in predicting crack detection by comparing with the existing CNN-only model. If the proposed method and experimental results obtained through this study are utilized, it can be applied in various fields such as the environment and humanities where time series data occurs frequently as well as crack data of concrete structures.