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A Correlation-Based Approach to Corrosion Detection with Lamb Wave Mode Cutoff

  • Xuwei Cao
  • Liang Zeng
  • Jing LinEmail author
  • Jiadong Hua
Article

Abstract

Time of flight and amplitude attenuation are commonly used features for corrosion detection in Lamb wave testing, but the sensitivity is limited by their individual application scenarios. The mode cutoff of Lamb waves is available and sensitive to determine and describe corrosion patches. In this paper, an approach is proposed by detecting envelope variations of a particular higher order mode after propagating through the inspected area. The excitation frequency is selected slightly above its cutoff frequency, leading to a preferable sensitivity for corrosion detection. After dispersion compensation and windowing, envelope difference coefficient is established as a correlation-based indicator to describe these variations. Such a technique could be used to scan multiple paths and provide a comprehensive corrosion map. Experiments are performed on a corroded aluminum plate. The interference from scattered components has also been discussed in detail. Based on our proposed indicator, the probability reconstruction algorithm provides an acceptable diagnosis map. In addition, the effectiveness of our indicator under different corrosion widths and depths is verified by a series of finite element simulations.

Keywords

Corrosion detection Nondestructive testing Mode cutoff Envelope difference coefficient Dispersion compensation 

Notes

Acknowledgements

The work is supported by the National Natural Science Foundation of China (Grant Nos. 51875435, 51421004), and the China Postdoctoral Science Foundation (Grant No. 2018M643627), which are highly appreciated by the authors.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Achenbach, J.D.: Quantitative nondestructive evaluation. Int. J. Solids Struct. 37(1–2), 13–27 (2000).  https://doi.org/10.1016/s0020-7683(99)00074-8 CrossRefzbMATHGoogle Scholar
  2. 2.
    Drinkwater, B.W., Wilcox, P.D.: Ultrasonic arrays for non-destructive evaluation: a review. NDT E Int. 39(7), 525–541 (2006).  https://doi.org/10.1016/j.ndteint.2006.03.006 CrossRefGoogle Scholar
  3. 3.
    Krautkrämer, J., Krautkrämer, H.: Ultrasonic Testing of Materials. Springer, Berlin (1990)CrossRefGoogle Scholar
  4. 4.
    Auld, B.A.: Acoustic Fields and Waves in Solids. Wiley, New York (1990)Google Scholar
  5. 5.
    Hutchins, D.A., Jansen, D.P., Edwards, C.: Lamb-wave tomography using non-contact transduction. Ultrasonics 31(2), 97–103 (1993).  https://doi.org/10.1016/0041-624x(93)90039-3 CrossRefGoogle Scholar
  6. 6.
    Pei, J., Yousuf, M.I., Degertekin, F.L., Honein, B.V., Khuri-Yakub, B.T.: Lamb wave tomography and its application in pipe erosion/corrosion monitoring. Res. Nondestruct. Eval. 8(4), 189–197 (1996).  https://doi.org/10.1007/BF02433949 CrossRefGoogle Scholar
  7. 7.
    Malyarenko, E.V., Hinders, M.K.: Fan beam and double crosshole Lamb wave tomography for mapping flaws in aging aircraft structures. J. Acoust. Soc. Am. 108(4), 1631–1639 (2000).  https://doi.org/10.1121/1.1289663 CrossRefGoogle Scholar
  8. 8.
    Leonard, K.R., Malyarenko, E.V., Hinders, M.K.: Ultrasonic Lamb wave tomography. Inverse Probl. 18(6), 1795–1808 (2002).  https://doi.org/10.1088/0266-5611/18/6/322 MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Belanger, P., Cawley, P.: Feasibility of low frequency straight-ray guided wave tomography. NDT E Int. 42(2), 113–119 (2009).  https://doi.org/10.1016/j.ndteint.2008.10.006 CrossRefGoogle Scholar
  10. 10.
    Huthwaite, P.: Improving accuracy through density correction in guided wave tomography. Proc. R. Soc. Lond. A 472(2186), 20150832 (2016).  https://doi.org/10.1098/rspa.2015.0832 MathSciNetCrossRefGoogle Scholar
  11. 11.
    Nagata Y, Huang J, Achenbach JD, Krishnaswamy S (1995) Lamb wave tomography using laser-based ultrasonics. In: Review of Progress in Quantitative Nondestructive Evaluation, vol. 14, pp. 561–568. Springer, Boston.  https://doi.org/10.1007/978-1-4615-1987-4_68 CrossRefGoogle Scholar
  12. 12.
    Leonard, K.R., Hinders, M.K.: Lamb wave tomography of pipe-like structures. Ultrasonics 43(7), 574–583 (2005).  https://doi.org/10.1016/j.ultras.2004.12.006 CrossRefGoogle Scholar
  13. 13.
    Ho, K.S., Billson, D.R., Hutchins, D.A.: Ultrasonic Lamb wave tomography using scanned EMATs and wavelet processing. Nondestruct. Test. Eval. 22(1), 19–34 (2007).  https://doi.org/10.1080/10589750701327890 CrossRefGoogle Scholar
  14. 14.
    Wright, W., Hutchins, D., Jansen, D., Schindel, D.: Air-coupled Lamb wave tomography. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 44(1), 53–59 (1997).  https://doi.org/10.1109/58.585190 CrossRefGoogle Scholar
  15. 15.
    Gao H, Shi Y, Rose JL (2005) Guided wave tomography on an aircraft wing with leave in place sensors. In: Review of Progress in Quantitative Nondestructive Evaluation, vol. 24, pp. 1788–1794. American Institute of Physics, New York.  https://doi.org/10.1063/1.1916887
  16. 16.
    Zhao, X., Gao, H., Zhang, G., Ayhan, B., Yan, F., Kwan, C., Rose, J.L.: Active health monitoring of an aircraft wing with embedded piezoelectric sensor/actuator network: I. Defect detection, localization and growth monitoring. Smart Mater. Struct. 16(4), 1208–1217 (2007).  https://doi.org/10.1088/0964-1726/16/4/032 CrossRefGoogle Scholar
  17. 17.
    Wang, D., Ye, L., Su, Z., Lu, Y., Li, F., Meng, G.: Probabilistic damage identification based on correlation analysis using guided wave signals in aluminum plates. Struct. Health Monit. 9(2), 133–144 (2010).  https://doi.org/10.1177/1475921709352145 CrossRefGoogle Scholar
  18. 18.
    Wang, D., Ye, L., Lu, Y., Li, F.: A damage diagnostic imaging algorithm based on the quantitative comparison of Lamb wave signals. Smart Mater. Struct. 19(6), 065008 (2010).  https://doi.org/10.1088/0964-1726/19/6/065008 CrossRefGoogle Scholar
  19. 19.
    Zeng, L., Lin, J., Hua, J., Shi, W.: Interference resisting design for guided wave tomography. Smart Mater. Struct. 22(5), 055017 (2013).  https://doi.org/10.1088/0964-1726/22/5/055017 CrossRefGoogle Scholar
  20. 20.
    Zhu, W., Rose, J.L., Barshinger, J.N., Agarwala, V.S.: Ultrasonic guided wave NDT for hidden corrosion detection. Res. Nondestruct. Eval. 10(4), 205–225 (1998).  https://doi.org/10.1080/09349849809409629 CrossRefGoogle Scholar
  21. 21.
    Rose JL, Barshinger J (1998) Using ultrasonic guided wave mode cutoff for corrosion detection and classification. In: Proceedings of the IEEE Ultrasonics Symposium, vol. 1, pp. 851–854. IEEE, New York.  https://doi.org/10.1109/ultsym.1998.762277
  22. 22.
    Tuzzeo, D., Scalea, F.L.D.: Noncontact air-coupled guided wave ultrasonics for detection of thinning defects in aluminum plates. Res. Nondestruct. Eval. 13(1), 61–77 (2001).  https://doi.org/10.1080/09349840108968178 CrossRefGoogle Scholar
  23. 23.
    Silva, M.Z., Gouyon, R., Lepoutre, F.: Hidden corrosion detection in aircraft aluminum structures using laser ultrasonics and wavelet transform signal analysis. Ultrasonics 41(4), 301–305 (2003).  https://doi.org/10.1016/s0041-624x(02)00455-9 CrossRefGoogle Scholar
  24. 24.
    Belanger, P.: High order shear horizontal modes for minimum remnant thickness. Ultrasonics 54(4), 1078–1087 (2014).  https://doi.org/10.1016/j.ultras.2013.12.013 CrossRefGoogle Scholar
  25. 25.
    Rose, J.L.: Ultrasonic Waves in Solid Media. Cambridge University Press, Cambridge (1999)Google Scholar
  26. 26.
    Holland, S.D., Chimenti, D.E.: Air-coupled acoustic imaging with zero-group-velocity Lamb modes. Appl. Phys. Lett. 83(13), 2704–2706 (2003).  https://doi.org/10.1063/1.1613046 CrossRefGoogle Scholar
  27. 27.
    Liu, L., Yuan, F.G.: A linear mapping technique for dispersion removal of Lamb waves. Struct. Health Monit. 9(1), 75–86 (2009).  https://doi.org/10.1177/1475921709341012 CrossRefGoogle Scholar
  28. 28.
    Michaels, J.E., Lee, S.J., Croxford, A.J., Wilcox, P.D.: Chirp excitation of ultrasonic guided waves. Ultrasonics 53(1), 265–270 (2013).  https://doi.org/10.1016/j.ultras.2012.06.010 CrossRefGoogle Scholar
  29. 29.
    Zhou, C., Su, Z., Cheng, L.: Probability-based diagnostic imaging using hybrid features extracted from ultrasonic Lamb wave signals. Smart Mater. Struct. 20(12), 125005 (2011).  https://doi.org/10.1088/0964-1726/20/12/125005 CrossRefGoogle Scholar
  30. 30.
    Huang, L., Zeng, L., Lin, J.: Baseline-free damage detection in composite plates based on the reciprocity principle. Smart Mater. Struct. 27(1), 015026 (2018).  https://doi.org/10.1088/1361-665x/aa9cc1 CrossRefGoogle Scholar
  31. 31.
    Pearce, J., Mittleman, D.: Defining the Fresnel zone for broadband radiation. Phys. Rev. E 66(5), 056602 (2002).  https://doi.org/10.1103/physreve.66.056602 CrossRefGoogle Scholar
  32. 32.
    Pavlakovic BN (1998) Leaky guided ultrasonic waves in NDT. Ph.D. thesis, Imperial College LondonGoogle Scholar

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Authors and Affiliations

  1. 1.Shaanxi Key Laboratory of Mechanical Product Quality Assurance and Diagnostics, State Key Laboratory of Manufacturing System Engineering, School of Mechanical EngineeringXi’an Jiaotong UniversityXi’anChina
  2. 2.Science & Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems EngineeringBeihang UniversityBeijingChina

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