DOI QR코드

DOI QR Code

Evaluation of crack opening phenomenon using subset-optimized digital image correlation

  • Kang, Myung Soo (Department of Architectural Engineering, Sejong University) ;
  • Im, Seok Been (2 Research Institute for Infrastructure Performance, KISTEC) ;
  • An, Yun-Kyu (Department of Architectural Engineering, Sejong University)
  • 투고 : 2020.05.14
  • 심사 : 2021.01.04
  • 발행 : 2021.05.25

초록

This paper presents crack opening phenomenon evaluation using digital image correlation (DIC) with a statistically optimized subset size. In conventional DIC analysis, the subset sizes varying from several pixels to more than hundred pixels have been often selected by experts' subjective judgement based on conventional subset size determination algorithms. Since these conventional subset size determination algorithms, however, calculate speckle pattern features at a certain location of a single target image, it is difficult to consider not only all speckle pattern features within region of interest (ROI) but also the random measurement noises during the digital image acquisition process. To overcome the technical limitation, a statistical optimization algorithm of the subset size, which calculates the optimal subset size by the 3-loop iteration of normalized cross correlation within the entire ROI, is newly proposed. In addition, the optimal subset-based DIC analysis is applied to crack opening phenomenon evaluation in a mock-up concrete specimen under step loading conditions. The validation test results show 3.6 ㎛ maximum error compared with the ground truth which is obtained by direct measurement, while a conventional subset size determination algorithm-based DIC analysis produces the maximum error of 62.7 ㎛.

키워드

과제정보

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2018R1A1A1A05078493).

참고문헌

  1. An, Y.K. and Sohn, H. (2015), "Visualization of non-propagating lamb wave modes for fatigue crack evaluation", J. Appl. Phys., 117, 114904. https://doi.org/10.1063/1.4906499
  2. An, Y.K., Park, B. and Sohn, H. (2013), "Complete noncontact laser ultrasonic imaging for automated crack visualization in a plate", Smart Mater. Struct., 22(2), 025022. https://doi.org/10.1088/0964-1726/22/2/025022
  3. An, Y.K., Yang, J., Hwang, S. and Sohn, H. (2015), "Line laser lock-in thermography for instantaneous imaging of cracks in semiconductor chips", Opt. Lasers Eng., 73, 128-136. https://doi.org/10.1016/j.optlaseng.2015.04.013
  4. Bohacova, M. (2013), "Methodology of short fatigue crack detection by the eddy current method in a multi-layered metal aircraft structure", Eng. Fail. Anal., 35(15), 597-608. https://doi.org/10.1016/j.engfailanal.2013.06.009
  5. Caizzone, S. and DiGiampaolo, E. (2015), "Wireless passive RFID crack width sensor for structural health monitoring", IEEE Sens J., 15(12), 6767-6774. https://doi.org/10.1109/JSEN.2015.2457455
  6. Camerini, C., Rebello, J.M.A., Braga, L., Santos, R., Chady, T., Psuj, G. and Pereira, G. (2018), "In-line inspection tool with eddy current instrumentation for fatigue crack detection", Sensors, 18(7), 2161. https://doi.org/10.3390/s18072161
  7. Destrebecq, J.F., Toussaint, E. and Ferrier, E. (2011), "Analysis of cracks and deformations in a full scale reinforced concrete beam using a digital image correlation technique", Experim. Mech., 51(6), 879-890. https://doi.org/10.1007/s11340-010-9384-9
  8. Ghorbani, R., Matta, F. and Sutton, M.A. (2014), "Full-field deformation measurement and crack mapping on confined masonry walls using digital image correlation", Experim. Mech., 55(1), 227-243. https://doi.org/10.1007/s11340-014-9906-y
  9. Giachetti, A. (2000), "Matching techniques to compute image motion", Image Vis Comput., 18(3), 247-260. https://doi.org/10.1016/S0262-8856(99)00018-9
  10. Hua, T., Xie, H., Wang, S., Hu, Z., Chen, P. and Zhang, Q. (2011), "Evaluation of the quality of a speckle pattern in the digital image correlation method by mean subset fluctuation", Opt. Laser Technol., 43(1), 9-13. https://doi.org/10.1016/j.optlastec.2010.04.010
  11. Hutt, T. and Cawley, P. (2009), "Feasibility of digital image correlation for detection of cracks at fastener holes", NDT & E Int., 42(2), 141-149. https://doi.org/10.1016/j.ndteint.2008.10.008
  12. Jang, K. and An, Y.K. (2018), "Multiple crack evaluation on concrete using a line laser thermography scanning system", Smart Struct. Syst., Int. J., 22(2), 201-207. https://doi.org/10.12989/sss.2018.22.2.201
  13. Kim, N., Jang, K. and An, Y.K. (2018), "Self-sensing nonlinear ultrasonic fatigue crack detection under temperature variation", Sensors, 18(8), 2527. https://doi.org/10.3390/s18082527
  14. Lecompte, D., Smits, A., Bossuyt, S., Sol, H., Vantomme, J., Van Hemelrijck, D. and Habraken, A.M. (2006), "Quality assessment of speckle patterns for digital image correlation", Opt. Laser Eng., 44(11), 1132-1145. https://doi.org/10.1016/j.optlaseng.2005.10.004
  15. Li, T., Almond, D.P. and Rees, D.A.S. (2011), "Crack imaging by scanning pulsed laser spot thermography", NDT & E Int., 44(2), 216-225. https://doi.org/10.1016/j.ndteint.2010.08.006
  16. Maragos, P. and Schafer, R. (1987), "Morphological filters-part I: their set-theoretic analysis and relations to linear shift-invariant filters", IEEE Trans. Signal Process., 35(8), 1153-1169. https://doi.org/10.1109/TASSP.1987.1165259
  17. Marindra, A.M.J. and Tian, G.Y. (2018), "Chipless RFID sensor tag for metal crack detection and characterization", IEEE T Microw Theory, 66(5), 2452-2462. https://doi.org/10.1109/TMTT.2017.2786696
  18. Meng, L., Jin, G. and Yao, X. (2006), "Errors caused by misalignment of the optical camera axis and the object surface in the DSCM", J. Tsinghua Univ., 46, 1930-1932. https://doi.org/10.3321/j.issn:1000-0054.2006.11.035
  19. Otsu, N. (1979), "A threshold selection method from gray level histograms", IEEE T. Syst. Man. Cybernet., 9(1), 62-66. https://doi.org/10.1109/TSMC.1979.4310076
  20. Pan, B., Xie, H., Wang, Z., Qian, K. and Wang, Z. (2008), "Study on subset size selection in digital image correlation for speckle patterns", Opt. Express, 16(10), 7037-7048. https://doi.org/10.1364/OE.16.007037
  21. Pour-Ghaz, M., Barrett, T., Ley, T., Materer, N., Apblett, A. and Weiss, J. (2014), "Wireless crack detection in concrete elements using conductive surface sensors and radio frequency identification technology", J. Mater. Civil Eng., 26(5), 923-929. https://doi.org/10.1061/(ASCE)MT.1943-5533.0000891
  22. Qaddoumi, N., Ranu, E., McColskey, J.D., Mirshahi, R. and Zoughi, R. (2000), "Microwave detection of stress-induced fatigue cracks in steel and potential for crack opening determination", Res. Nondestruct. Eval., 12(2), 87-103. https://doi.org/10.1080/09349840009409652
  23. Schreier, H.W. and Sutton, M.A. (2002), "Systematic errors in digital image correlation due to undermatched subset shape functions", Experim. Mech., 42, 303-310. https://doi.org/10.1007/BF02410987
  24. Yaofeng, Y.F. and Pang, H.J. (2007), "Study of optimal subset size in digital image correlation of speckle pattern images", Opt. Lasers Eng., 45, 967-974. https://doi.org/10.1016/j.optlaseng.2007.01.012
  25. Sutton, M.A., McNeill, S.R., Jang, J. and Babai, M. (1988), "Effects of subpixel image restoration on digital correlation error estimates", Opt. Eng., 27, 870-877. https://doi.org/10.1117/12.7976778
  26. Tong, W. (2005), "An evaluation of digital image correlation criteria for strain mapping applications", Strain, 41(4), 167-175. https://doi.org/10.1111/j.1475-1305.2005.00227.x
  27. Tsukamoto, A., Hato, T., Adachi, S., Oshikubo, Y., Tsukada, K. and Tanabe, K. (2018), "Development of eddy current testing system using HTS-SQUID on a hand cart for detection of fatigue cracks of steel plate used in expressways", IEEE T. Appl. Superconduct., 28(4), 1-5. https://doi.org/10.1109/TASC.2018.2795614
  28. Wang, Z.Y., Li, H.Q., Tong, J.W. and Ruan, J.T. (2007), "Statistical analysis of the effect of intensity pattern noise on the displacement measurement precision of digital image correlation using self-correlated images", Expim. Mech., 47(5), 701-707. https://doi.org/10.1007/s11340-006-9005-9
  29. Yaofeng, S. and Pang, J.H.L. (2007), "Study of optimal subset size in digital image correlation of speckle pattern images", Opt. Laser Eng., 45(9), 967-974. https://doi.org/10.1016/j.optlaseng.2007.01.012
  30. Yun, T. and Lim, S. (2014), "High-Q and miniaturized complementary split ring resonator-loaded substrate integrated waveguide microwave sensor for crack detection in metallic materials", Sensor Actuat. A-Phys., 214, 25-30. https://doi.org/10.1016/j.sna.2014.04.006