• Title/Summary/Keyword: 레일표면결함

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Principle and Applications of Induction Infrared Thermography (유도 적외선 열화상 기법의 원리와 적용)

  • Kim, Wontae
    • Journal of the Korean Society for Nondestructive Testing
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    • v.37 no.1
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    • pp.44-49
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    • 2017
  • 본고에서는 열유도 적외선 열화상 기법의 원리와 응용에 있어 기초적인 개념, 특정 상태량 및 실험적 기법에 대하여 소개하도록 한다. 유도 열화상 기법에 적용되는 유도 주파수의 범위는 1500 Hz ~ 52 MHz이며 강자성 강재 단조 부품의 표면결함 검출에 사용되어진다. 균열 검출 감도는 자분탐상기법과 유사하나 필요한 경우 유도 주파수를 낮춤으로서 강재에 숨겨진 결함을 검출할 수 있다. 탄소섬유강화폴리머(CFRP)에서는 섬유 결함을 검출하며, 실리콘 태양 전지에서는 양호한 열적 콘트라스트와 함께 균열을 검출한다. 유도 열화상 기법의 향 후 대표적인 활용분야로는 레일 및 휠과 같은 철도 구성요소에서의 결함 탐상이 있다[1].

Rolling Contact Fatigue Analysis According to Defect Size on Rail (레일의 표면결함크기에 따른 구름접촉수명평가)

  • Seo, Jung-Won;Kwon, Seong-Tae;Lee, Dong-Heong;Kwon, Seok-Jin
    • Proceedings of the KSR Conference
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    • 2011.10a
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    • pp.637-642
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    • 2011
  • Rails are subjected to damage from rolling contact fatigue, which leads to defects such as cracks. Rolling contact fatigue damages on the surface of rail such as head check, squats are one of growing problems. Another form of rail surface damage, known as "Ballast imprint" has become apparent. This form of damage is associated with ballast particles becoming trapped between the wheel and the surface of rail. These defects are still one of the key reasons for rail maintenance and replacement. In this study, we have investigated whether the ballast imprint is an initiator of head check type cracks and effect of defect size using Finite element analysis. The FE analysis were used to investigate stresses and strains in subsurface of defects according to variation of defect size. Based on loading cycles obtained from FE analysis, fatigue analysis for each point was carried out.

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Rail Surface Defect Detection System of Next-Generation High Speed Train (차세대 고속열차의 레일표면 결함 검출 시스템)

  • Choi, Woo-Yong;Kim, Jeong-Yeon;Yang, Il-Dong
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.5
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    • pp.870-876
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    • 2017
  • In this paper, we proposed the automatic vision inspection system using multi-layer perceptron to detect the defects occurred on rail surface. The proposed system consists of image acquisition part and analysis part. Rail surface image is acquired as equal interval using line scan camera and lighting. Mean filter and dynamic threshold is used to reduce noise and segment defect area. Various features to characterize the defects are extracted. And they are used to train and distinguish defects by MLP-classifier. The system is installed on HEMU-430X and applied to analyze the rail surface images acquired from Honam-line at high speed up to 300 km/h. Recognition rate is calculated through comparison with manual inspection results.