Skip to main content
SpringerLink
Log in

Image Processing Algorithm for Real-Time Crack Inspection in Hole Expansion Test

  • Regular Paper
  • Published:
International Journal of Precision Engineering and Manufacturing Aims and scope Submit manuscript

Abstract

This paper mainly focuses on development of the smart crack inspection algorithm facilitating the through-thickness crack during the hole expansion test, which makes it possible to calculate the hole expansion ratio, automatically, with the image processing technique. The proposed crack inspection algorithm consists of six steps such as binarization, blob detection, background deletion, ROI selection, image linearization, and crack identification using the C# language. This algorithm is able to capture the various types of the through-thickness and double cracks irrespective of the reflectance and the initial thickness of the applied sheet materials. In addition, it is possible to keep trace of the in-plane crack and its propagation during the HER test.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  1. Yoon, J., & Lee, J. (2015). Process design of warm-forging with extruded Mg-8Al-0.5 Zn alloy for differential case in automobile transmission. International Journal of Precision Engineering and Manufacturing, 16(4), 841–846.

    Article  Google Scholar 

  2. Yoon, J., & Lee, S.-I. (2015). Warm forging of magnesium AZ80 alloy for the control arm in an automobile. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 229(13), 1732–1738.

    Google Scholar 

  3. Won, C., et al. (2018). Stripping failure of punching pin in GPa-grade steels. The International Journal of Advanced Manufacturing Technology, 94(1–4), 73–83.

    Article  Google Scholar 

  4. Park, J.-H., & Kim, K. J. (2013). Optimal design of camber link component for light weight automobile using CAE (Computer Aided Engineering). International Journal of Precision Engineering and Manufacturing, 14(8), 1433–1437.

    Article  Google Scholar 

  5. Jiang, C., et al. (2012). Hot stamping die design for vehicle door beams using ultra-high strength steel. International Journal of Precision Engineering and Manufacturing, 13(7), 1101–1106.

    Article  Google Scholar 

  6. Yıldız, B. S. (2017). Natural frequency optimization of vehicle components using the interior search algorithm. Materials Testing, 59(5), 456–458.

    Article  Google Scholar 

  7. Gökdağ, H., & Yildiz, A. R. (2012). Structural damage detection using modal parameters and particle swarm optimization. Materials Testing, 54(6), 416–420.

    Article  Google Scholar 

  8. Xu, L., Frédéric, B., & Lee, M.-G. (2012). Hole expansion of twinning-induced plasticity steel. Scripta Materialia, 66(12), 1012–1017.

    Article  Google Scholar 

  9. Thomas, D. J. (2009). Characteristics of abrasive waterjet cut-edges and the effect on formability and fatigue performance of high strength steels. Journal of Manufacturing Processes, 11(2), 97–105.

    Article  Google Scholar 

  10. Krempaszky, C., Larour, P., Freudenthaler, J., & Werner, E., (2014). Towards more efficient hole expansion testing. In IDDRG conference (pp. 204–209).

  11. Yoon, J. I., et al. (2016). Factors governing hole expansion ratio of steel sheets with smooth sheared edge. Metals and Materials International, 22(6), 1009–1014.

    Article  Google Scholar 

  12. Karelova, A., et al. (2009). Hole expansion of dual-phase and complex-phase ahs steels-effect of edge conditions. Steel Research International, 80(1), 71–77.

    Google Scholar 

  13. Fang, X., et al. (2003). The relationships between tensile properties and hole expansion property of C-Mn steels. Journal Materials Science, 38(18), 3877–3882.

    Article  Google Scholar 

  14. Sugimoto, K., et al. (2000). Stretch-flangeability of a high-strength TRIP type bainitic sheet steel. ISIJ International, 40(9), 920–926.

    Article  Google Scholar 

  15. De, S. K., et al. (2011). Assessment of formability of hot-rolled steel through determination of hole-expansion ratio. Materials and Manufacturing Processes, 26(1), 37–42.

    Article  Google Scholar 

  16. Krawczyk, J., et al. (2016). The influence of the punch shape and the cutting method on the limit strain in the hole expansion test. Key Engineering Materials, 716, 129.

    Article  Google Scholar 

  17. Tsoupis, I., & Merklein, M. (2016). Edge crack sensitivity of lightweight materials under different load conditions. IOP Conference Series: Materials Science and Engineering, 159(1), 012017.

    Article  Google Scholar 

  18. ISO 16630. (2009). Metallic materials —Sheet and strip —Hole expanding test. Geneva: ISO - International Organization for Standardization.

    Google Scholar 

  19. Kim, H., et al. (2016). Development of new hole expansion testing method. Journal of Physics: Conference Series, 734(3), 032025.

    Google Scholar 

  20. Dünckelmeyer, M., et al. (2009). Instrumented hole expansion test. In Proceeding of international doctoral seminar (Vol. 2009).

  21. Wang, K., Luo, M., & Wierzbicki, T. (2014). Experiments and modeling of edge fracture for an AHSS sheet. International Journal of Fracture, 187(2), 245–268.

    Article  Google Scholar 

  22. Chen, X, et al. (2011). Measurement of strain distribution for hole expansion with digital image correlation (DIC) system. SAE Technical Paper, No. 2011-01-0993.

  23. Oh, S. H., Yang, S. H., & Kim, Y. S. (2015). A study of image processing based hole expansion test. Testing and Measurement: Techniques and Applications-Chan (Ed.), 349–354.

    Google Scholar 

  24. Watanabe, M, & Nayar, S. K. (1996). Telecentric optics for computational vision. In European conference on computer vision. Berlin: Springer.

  25. Bing, P., Hui-Min, X., Bo-Qin, X., & Fu-Long, D. (2006). Performance of sub-pixel registration algorithms in digital image correlation. Measurement Science and Technology, 17(6), 1615–1621.

    Article  Google Scholar 

  26. Sauvola, J., & Pietikäinen, M. (2000). Adaptive document image binarization. Pattern Recognition, 33(2), 225–236.

    Article  Google Scholar 

Download references

Acknowledgements

Author Prof. Jonghun Yoon has received a research funding from the National Research Foundation of Korea (NRF) Grant funded by the Korea government (2016R1C1B1006875), and the “Human Resource Program in Energy Technology” of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted by the Ministry of Trade, Industry & Energy (20174010201310). The authors declare that they have no conflict of interest.

Author information

Authors and Affiliations

  1. Department of Mechanical Design Engineering, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of Korea

    Seungho Choi & Kwangyoon Kim

  2. Chonro Scientific Co., Ltd. (CRS), 44-18, Hoguk-ro 429beon-gil, Soheul-eup, Pocheon-si, Gyeonggi-do, 11184, Republic of Korea

    Jaeho Lee

  3. School of Materials Science and Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu, 41566, Republic of Korea

    Sung Hyuk Park

  4. Korea Institute of Industrial Technology Metal Forming R&D Group, 156, Gaetbeol-ro (Songdo-Dong), Yeonsu-gu, Incheon, 21999, Republic of Korea

    Hye-Jin Lee

  5. Department of Mechanical Engineering, Hanyang University, 55 Hanyangdaehak-ro, Sangnok-gu, Ansan-si, Gyeonggi-do, 15588, Republic of Korea

    Jonghun Yoon

Authors
  1. Seungho Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kwangyoon Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jaeho Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sung Hyuk Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hye-Jin Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jonghun Yoon
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jonghun Yoon.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Choi, S., Kim, K., Lee, J. et al. Image Processing Algorithm for Real-Time Crack Inspection in Hole Expansion Test. Int. J. Precis. Eng. Manuf. 20, 1139–1148 (2019). https://doi.org/10.1007/s12541-019-00101-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12541-019-00101-4

Keywords

Search

Navigation