Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Type Classification and Shape Display of Brazing Defect in Heat Exchanger

열교환기 브레이징 결함의 유형 분류 및 형상 디스플레이

  • 김진영 (동명대학교 메카트로닉스공학과)
  • Received : 2012.09.01
  • Accepted : 2013.01.08
  • Published : 2013.02.01
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Abstract

X-ray cross-sectional image-based inspection technique is one of the most useful methods to inspect the brazing joints of heat exchanger. Through X-ray cross-sectional image acquisition, image processing, and defect inspection, the defects of brazing joints can be detected. This paper presents a method to judge the type of detected defects automatically, and to display them three-dimensionally. The defect type is classified as unconnected defect, void, and so on, based on location, size, and shape information of defect. Three-dimensional display which is realized using OpenGL (Open Graphics Library) will be helpful to understand the overall situation including location, size, shape of the defects in a test object.

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References

  1. D. Robinson, "Identification and sizing of defects in metallic pipes by remote field eddy current inspection," Tunnelling and Underground Space Technology, vol. 13, no. 2, pp. 17-27, 1998. https://doi.org/10.1016/S0886-7798(98)00090-X
  2. T. D'Orazio, M. Leo, A. Distante, C. Guaragnella, V. Pianese, and G. Cavaccini, "Automatic ultrasonic inspection for internal defect detection in composite materials," NDT & E International, vol. 41, no 2, pp. 145-154, 2008. https://doi.org/10.1016/j.ndteint.2007.08.001
  3. Z. Han, H. Luo, J. Cao, and H. Wang, "Acoustic emission during fatigue crack propagation in a micro-alloyed steel and welds," Materials Science and Engineering, vol. 528, no. 25-26, pp. 7751-7756, 2011. https://doi.org/10.1016/j.msea.2011.06.065
  4. I. Valavanis and D. Kosmopoulos, "Multiclass defect detection and classification in weld radiographic images using geometric and texture features," NDT & E International, vol. 38, no. 7, pp. 522-528, 2005. https://doi.org/10.1016/j.ndteint.2005.01.011
  5. J. Y. Kim and S. W. Seo, "Defect detection of brazing joint in heat exchanger using X-ray image," Journal of Control, Automation and System Engineering, vol. 17, no. 10, pp. 1044-1050, 2011.
  6. J. Y. Kang, "Brazing defect," J. of the Korean Welding Society, vol. 18, no. 2, pp. 11-13, Dec. 2000.
  7. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice Hall, 2008.
  8. L. He, Y. Chao, and K. Suzuki, "An efficient first-scan method for label-equivalence-based labeling algorithms," Pattern Recognition Letters, vol. 31, no. 1, pp. 28-35, 2010. https://doi.org/10.1016/j.patrec.2009.08.012
  9. M. P. Baker and D. Hearm, Computer Graphics with openGL, Prentice Hall, 2004.
  10. E. Lengyel, The OpenGL Extensions Guide, Charles River Media, 2003.