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Application of Modal Acoustic Emission Technique for Recognition of Corrosion Severity on a Thin Plate

  • Weigang ZhangEmail author
  • Jie Geng
  • Yanting Xu
Conference paper
Part of the Springer Proceedings in Physics book series (SPPHY, volume 218)

Abstract

Corrosion poses a significant safety inspection problem in large industrial structures, where access for conventional inspection techniques is very limited. The theory of modal acoustic emission (MAE) was used to recognize the correlation between corrosion severity and the waveform of signals. The particle displacements of plates were investigated theoretically. The chemical reaction between hydrochloric acid and a steel plate was used to simulate the corrosion process. The amplitude difference of the extensional (S0) and the flexural wave mode (A0) was analyzed. It found that when the corrosion depth was slight, no matter its surface was large or small, the amplitude difference had almost no difference. When the corrosion depth reached to two thirds of the thin plate, the amplitude difference was almost half the amplitude of S0 in small surface corrosion pits, while the amplitude difference reached to 1.5 times of S0 in large surface pits. As a conclusion, the MAE technique is able to detect the plate-like structure corrosion in a long distance, and the amplitude of A0 is identified as the critical index for the corrosion severity.

Keywords

Modal acoustic emission Corrosion Wave propagation Lamb wave 

References

  1. 1.
    H. Bi, Z. Li, J. Liu, Y. Cheng, I. Toku-Gyamerah, Study on pitting corrosion of storage tank bottom steel in acidic condition using acoustic emission. Int. J. Electrochem. Sci 10, 4416–4427 (2015)Google Scholar
  2. 2.
    F. Yeo, P. Fromme, Guided ultrasonic wave inspection of corrosion at ship hull structures, in AIP Conference Proceedings, vol. 820(1), (American Institute of Physics, College Park, MD, 2006), pp. 202–209CrossRefGoogle Scholar
  3. 3.
    A. Pau, D.V. Achillopoulou, F. Vestroni, Scattering of guided shear waves in plates with discontinuities. NDT E Int. 84, 67–75 (2016)CrossRefGoogle Scholar
  4. 4.
    M.R. Gorman, W.H. Prosser, AE source orientation by plate wave analysis. J. Acoust. Emission 9(4), 283–288 (1991)Google Scholar
  5. 5.
    M. Surgeon, M. Wevers, Modal analysis of acoustic emission signals from CFRP laminates. NDT E Int. 32(6), 311–322 (1999)CrossRefGoogle Scholar
  6. 6.
    M.R. Gorman, Plate wave acoustic emission. J. Acoust. Soc. Am. 90(1), 358–364 (1991)ADSCrossRefGoogle Scholar
  7. 7.
    W.H. Prosser, Advanced AE techniques in composite materials research. J. Acoust. Emission 14, 3–4 (1996)Google Scholar
  8. 8.
    O.V. Nedzvetskaya, G.A. Budenkov, A.V. Sokolkin, I.Y. Ievlev, Calculation of the acoustic channel in acoustic emission testing of bottoms of vertical steel tanks. Russ. J. Nondestr. Testing 39(10), 772–781 (2003)CrossRefGoogle Scholar
  9. 9.
    Y. Ding, R.L. Reuben, J.A. Steel, A new method for waveform analysis for estimating AE wave arrival time using wavelet decomposition. NDT E Int. 37(4), 279–290 (2004)CrossRefGoogle Scholar
  10. 10.
    D.G. Aggelis, T.E. Matikas, Effect of plate wave dispersion on the acoustic emission parameters in metals. Comput. Struct. 98, 17–22 (2012)CrossRefGoogle Scholar
  11. 11.
    O. Diligent, T. Grahn, A. Bostrom, P. Cawley, M.J.S. Lowe, The low-frequency reflection and scattering of the S0 lamb mode from a circular through-thickness hole in a plate: Finite element, analytical and experimental studies. J. Acoust. Soc. Am. 112(6), 2589–2601 (2002)ADSCrossRefGoogle Scholar
  12. 12.
    A. Mostafapour, S. Davoodi, Continuous leakage location in noisy environment using modal and wavelet analysis with one AE sensor. Ultrasonics 62, 305–311 (2015)CrossRefGoogle Scholar
  13. 13.
    C. Jirarungsatian, A. Prateepasen, Pitting and uniform corrosion source recognition using acoustic emission parameters. Corros. Sci. 52, 187–197 (2010)CrossRefGoogle Scholar
  14. 14.
    A. Prateepasen, C. Jirarungsatian, Implementation of acoustic emission source recognition for corrosion severity prediction. Corrosion 67(5), 056001–056001 (2011)CrossRefGoogle Scholar
  15. 15.
    V.V. Nosov, I.N. Burakov, Use of amplitude distribution parameters of acoustic emission signals for assessing the strength of structural materials. Russ. J. Nondestr. Testing 40(3), 157–162 (2004)CrossRefGoogle Scholar
  16. 16.
    H. Chou, M. Takemoto, Estimation of acoustic properties and fracture dynamics of polycrystalline graphites by AE signal processing. NDT E Int. 24(2), 67–74 (1994)CrossRefGoogle Scholar
  17. 17.
    K. Graff, Wave Motion in Elastic Solids (Oxford University Press, Ohio, USA, 1991)zbMATHGoogle Scholar
  18. 18.
    Y.P. Kim, M. Fregonese, H. Mazille, D. Feron, G. Santarini, Study of oxygen reduction on stainless steel surface and its contribution to acoustic emission recorded during corrosion processes. Corros. Sci. 48(12), 3945–3955 (2006)CrossRefGoogle Scholar
  19. 19.
    Y.P. Kim, M. Fregoneses, H. Mazille, D. Feron, G. Santarini, Ability of acoustic emission technique for detection and monitoring of crevice corrosion on 304L austenitic stainless steel. NDT E Int. 36(8), 553–561 (2003)CrossRefGoogle Scholar
  20. 20.
    K.M. Holford, A.W. Davies, R. Pullin, D.C. Carter, Damage location in steel bridges by acoustic emission. J. Intell. Mater. Syst. Struct. 12(8), 567–576 (2001)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.College of Quality and Safety EngineeringChina Jiliang UniversityHangzhouChina
  2. 2.Zhejiang Provincial Special Equipment Inspection and Research InstituteHangzhouChina

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