• Journal of Welding and Joining
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• v.9 no.3
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• pp.10-17
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• 1991

용접구조물에서 용접이음부가 차지하는 비율은 매우 작은 경우가 많지만 용접이음부에는 각종 초기결함(이들 결함으로부터 진전하는 피로 균열, 환경에 의한 균열등을 포함) 및 용접 초기의 부정형을 비롯해서 형상적 불연속 등에서 유기되는 국부적인 응력, 변형률의 집중, 잔류응력, 구속응력, 용접금속이 갖는 숙명적인 야금적 특성의 불균일, bond부 및 HAZ부에서의 용접열 싸이클에 의한 재질의 국부적 강도저하등 용접부의 강도를 저하시키는 인자들이 복합되기 쉽고, 용접구조물 전체의 내파괴 건전성평가에서 용접부가 파괴 강도는 매우 중요하다. 용접구조물의 설계, 시공의 목적은 소요성능의 확보에 있고 구조물이 사용중에 성능손실이나 불안정 파괴가 발생하지 않도록 하는 것이 주요요건이 될 것이다. 현재의 제강기술수준에서 볼 때 모재의 강 도보다 오히려 용접부의 강도 특히 피로강도 및 파괴 인성을 적절하고 합리적으로 평가하는 것이 매우 중요하다고 해도 과언이 아닐 것이다. 용접부의 강도를 평가하는데 있어서 용접부에 발 생하는 용접결함에 대한 평가는 매우 중요하며 이들 결함에 대한 허용결함한계를 평가하여 보수 여부 및 용접구조물의 신뢰성을 평가 할 필요가 있다.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.127-129
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• 2005

본 연구에서는 백라이트 유닛의 검사를 위한 머신비전 시스템을 구축한다. 시스템은 크게 하드웨어와 소프트웨어로 나눌 수 있고 하드웨어는 조명부, 영상획득부, 로봇 암 제어부로 분류된다. 조명부는 36W FPL램프로 구성되었고 조명부의 상판에 아크릴판을 거치대로 이용하여 백라이트 유닛을 거치한다. 로봇 암 제어부는 2축 로봇 암을 제어하여 로봇 암의 센서부착 지지대에 부착된 CCD 센서를 이동시킨다. 이와 동시에 영상획득부에서는 이미지를 획득하여 PC로 전송한다. 소프트웨어의 화상처리 검사 알고리즘은 일정 패턴이 있는 도광판에 대한 검사 알고리즘과 일정패턴이 없근 백라이트 유닛에 대한 검사 알고리즘으로 분리된다. 일정 패턴이 인쇄되어 있는 패널에 대한 검사 알고리즘은 모폴로지 연산을 이용하는 템플릿 체크방법과 블록 매칭 방법이 사용되었고 일정패턴이 없는 유닛에 대한 검사는 개선된 Otsu 방법을 이용하여 얼룩이나 흐릿한 결함에 대한 결함을 검출하였다. 실험결과 불균일한 결함과 밝기가 일정하지 않은 결함일지라고 90% 이상의 검출율로 뛰어난 성능을 입증하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.10
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• pp.1227-1234
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• 2012

In this study, fatigue tests were carried out using real-scale pipe bend specimens with wall-thinning defects under a cyclic bending load together with a constant internal pressure of 10 MPa. The wall-thinning defect was located at the extrados and the intrados of the pipe bend specimens. A fully reversed cyclic in-plane bending displacement was applied to the specimens. For the pipe bends with wall thinning at the extrados, an axial crack occurred at the crown of the pipe bend rather than at the extrados where the defect was located. In addition, the fatigue life was longer than that of a sound pipe bend predicted from the design fatigue curve in ASME Sec.III, and it was less dependent on the axial length of the wall-thinning defect. For the pipe bends with wall thinning at the intrados, a circumferential crack occurred at the intrados. In this case, the fatigue life was much shorter than that of a sound pipe bend predicted from the design fatigue curve, and it clearly decreased with decreasing axial length of the wall-thinning defect.

• Journal of the KSME
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• v.33 no.5
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• pp.435-448
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• 1993

용접부결함은 구조물 건전성측면에서 항상 문제가 되어 왔다. 따라서 용접시 발생 할 수 있는 결함들을 사전에 방지하기 위한 대책들이 꾸준히 연구되어 왔으며, 용접부의 최종 품질확인 및 부품 사용중 용접부의 건전성을 평가하기 위한 수단으로 비파괴시험법들이 오래전부터 적용되어 왔다. 따라서 이 글에서는 용접부의 특성, 용접부결함의 중요성에 대해 기술하고 부품 건전성의 진단목적으로 결함의 유무 및 크기측정을 위해 사용되는 비파괴시험법의 종류 및 특징, 비파괴 시험법 중에서 결함의 길이 및 두께방향의 높이측정을 위해 유일하게 이용되는 초음파시험법에 대해, 특히 결함크기 측정법 중 현재 널리 사용되는 몇 가지 방법에 대해 소개하고자 한다.

• Journal of the Korean Recycled Construction Resources Institute
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• v.8 no.3
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• pp.372-378
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• 2020

In this study, an experiment was conducted on the development and performance of self-propelled vehicles to repair defects in concrete sewage pipes. The self-propelled vehicle for a non-excavation repair for the sewage pipe defects was developed in consideration of the performance of the driving system, the feasibility of the repair unit, and the transportation of repair materials. In order to evaluate the performance of the developed self-propelled vehicle, a repair test was performed by simulating a defect at a connection between the main pipe and extruded one. The main sewage pipe was meade of concrete and its diameter was 500mm. Thereafter, watertightness performance was evaluated on the leakage at the repaired part. For watertightness performance, both ends of concrete sewage pipe and connected one was inserted by plugs, and then water was injected. The amount of leakage water measurement was 0.07L/㎡, indicating a value less than 0.2L/㎡ of the allowable leakage amount. Therefore, test results indicated that the self-propelled vehicle developed in this study exhibited excellent maintenance performance for repairing the sewage pipes.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.5
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• pp.536-542
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• 2011

Dissimilar metal welds in nuclear power plant are known as very susceptible to PWSCC flaws, and periodically inspected by the qualified inspector and qualified procedure during in-service inspection period. According to field survey data, the majority of their DMWs are located on tapered nozzle or adjacent to a tapered component. These types of configurations restrict examination access and also limit examination volume coverage. Additionally, circumferential scan for axially oriented flaw is very difficult to detect located on tapered surface because the transducer can't receive flaw response from reflector for miss-orientation. To overcome this miss-orientation, it is necessary adapt skewed ultrasonic transducer accomodate tapered surface. The skewed refracted longitudinal ultrasonic transducer designed by modeling and manufactured from the modelling result for axial flaw detection. Experimental results showed that the skewed refracted longitudinal ultrasonic transducer get higher flaw response than non-skewed refracted longitudinal ultrasonic transducer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.225-232
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• 2010

In this study, an automated ultrasonic testing system and post signal and image processing techniques are developed in order to construct ultrasonic flaw images in weldments. Image processing algorithms are built into the flaw image processing system for the automated ultrasonic testing system. The developed signal and image analysis algorithms addressed in this study include an A-Scan data compression algorithm, ultrasonic image amplification algorithm and B-scan flaw image correction algorithm(SAFT). This flaw image processing system for the automated ultrasonic testing system can be applied to various inspection fields.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.53-60
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• 2020

The bogies of railway vehicles are one of the most critical components for service. Fatigue defects in the bogie can be initiated for various reasons, such as material imperfection, welding defects, and unpredictable and excessive overloads during operation. To prevent the derailment of a railway vehicle, it is necessary to evaluate and detect the defect of a connection weldment between the car body and bogie accurately. The safety of the bogie weldment was checked using an ultrasonic test, and it is necessary to determine the occurrence of defects using a learning method. Recently, studies on deep learning have been performed to identify defects with a high recognition rate with respect to a fine and similar defect. In this paper, the databases of weldment specimens with artificial defects were constructed to detect the defect of a bogie weldment. The ultrasonic inspection using the wedge angle was performed to understand the detection ability of fatigue cracks. In addition, the convolutional neural network was applied to minimize human error during the inspection. The results showed that the defects of connection weldment between the car body and bogie could be classified with more than 99.98% accuracy using CNN, and the effectiveness can be verified in the case of an inspection.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.1
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• pp.11-22
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• 1997

It is very essential to get the accurate classification of defects in primary pressure vessel and piping welds for the safety of nuclear power plant. Ultrasonic testing has been widely applied to inspect primary pressure vessel and piping welds of nuclear power plants during PSI / ISI. Classification of flaws in weldments from their ultrasonic scattering signals is very important in quantitative nondestructive evaluation. This problem is ideally suited to a modern ultrasonic Pattern recognition technique. Here, a brief discussion on systematic approach to this methodology is presented including ultrasonic feature extraction, feature selection and classification. A stronger emphasis is placed on Fuzzy-UTSCS (UT signal classification system) as efficient classifiers for many practical classification problems. As an example Fuzzy-UTSCS is applied to classify flaws in ferrite pressure vessel weldments into two types such as linear and volumetric. It is shown that Fuzzy-UTSCS is able to exhibit higher performance than other classifiers in the defect classification.

• Journal of Korean Society of Steel Construction
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• v.11 no.1 s.38
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• pp.1-11
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• 1999

The aim of this study is to construct a machine vision monitoring system for an automatic visual inspection of weld joint in steel structure. An image processing algorithm for a visual weld defects detection on weld bead is developed using the intensity image. An optic system for getting four intensity images was set as a fixed camera position and four different illumination directions. The input images were thresholded and segmented after a suitable preprocessing and the features of each region were defined and calculated. The features were used in the detection and the classification of the visual weld defects. It is confirmed that the developed algorithm can detect weld defects that could not be detected by previously developed techniques. The recognized results were evaluated and compared to expert inspectors' results.