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JRM Vol.21 No.5 pp. 568-573
doi: 10.20965/jrm.2009.p0568
(2009)

Paper:

Detection Principle of Shape and Orientation of Corrosive Defects Using Lamb Waves

Chunguang Xu*, Joseph L. Rose**, and Xiang Zhao***

*School of Mechanical and Vehicular Engineering, Beijing Institute of Technology

**Department of Engineering Science and Mechanics, Pennsylvania State University

***FBS Inc.

Received:
March 12, 2009
Accepted:
June 1, 2009
Published:
October 20, 2009
Keywords:
defect, shape, orientation, Lamb wave, corrosion
Abstract

The shape and orientation of corrosive defects are critical in the evaluation of the reliability and durability of plate-like structures. And Lamb wave is considered as an effective tool for inspections of this kind corrosive plates. In this paper, the shape and orientation of plane defects are detected and presented using a circular transducer array with Lamb wave tomography approach. Here, considering a special shape defect with two-dimensions elliptical contour in the plate, the various ratios for both defect shape and orientation, individually representing different classifications of defects, is identified and investigated using Lamb wave tomography approach. And the validity of this approach has been proved through simulation experiments.

Cite this article as:
Chunguang Xu, Joseph L. Rose, , and Xiang Zhao, “Detection Principle of Shape and Orientation of Corrosive Defects Using Lamb Waves,” J. Robot. Mechatron., Vol.21, No.5, pp. 568-573, 2009.
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References
  1. [1] J. L. Rose, “Ultrasonic Waves in Solid Media,” Cambridge University Press, 1999.
  2. [2] T. Kundu, “Ultrasonic Nondestructive Evaluation-Engineering and Biological Material Characterization,” CRC Press, 2004.
  3. [3] L. W. Schmerr Jr. and S.-J. Song, “Ultrasonic Nondestructive Evaluation Systems-Models and Measurements,” Springer, 2007.
  4. [4] L. W. Schmerr Jr., “Fundamentals of Ultrasonic Nondestructive Evaluation-A Modeling Approach,” Iowa State University, 1998.
  5. [5] K. F. Graff, “Wave Motion in Elastic Solids,” Dover Publications Inc. New York, 1975.
  6. [6] K. Edalati, A. Kermani, B. Naderi, and B. Panahi, “Defects Evaluation in Lamb Wave Testing of Thin Plates,” www.ndt.net-3rd MENDT-Middle East Nondestructive Testing Conf. & Exhibition, pp. 27-30, Nov., 2005 Bahrain, Manama.
  7. [7] J. Rose, S. Pelts, and Y. Chao, “Modeling for flaw sizing potential with guided waves,” J. Nondes. Eval., Vol.19, pp. 55-66, 2002.
  8. [8] X. Zhao and J. L. Rose, “Three dimensional defect in a plate boundary element modeling for guided wave scattering,” Key Engineering Materials, Vol.270-273, pp. 453-460, 2004.
  9. [9] Y. Cho, D. D. Hongerholt, and J. L. Rose, “Lamb Wave Scattering Analysis for Reflector Characterization,” IEEE Tran. Ultra. Ferr. and Freq. Cont., Vol.44, pp. 44-52, 1997.
  10. [10] B. C. Lee and W. J. Staszewski, “Modelling of Lamb waves for damage detection in metallic structures: Part I. Wave propagation,” Smart Material And Structure, Vol.12, pp. 804-814, 2003.
  11. [11] B. C. Lee and W. J. Staszewski, “Modelling of Lamb waves for damage detection in metallic structures Part II. Wave interactions with damage,” Smart Material And Structure, Vol.12, pp. 815-824, 2003.
  12. [12] B. C. Lee and W. J. Staszewski, “Lamb wave propagation modelling for damage detection: I. Two-dimensional analysis,” Smart Material And Structure, Vol.16, pp. 249-259, 2007.
  13. [13] B. C. Lee and W. J. Staszewski, “Lamb wave propagation modelling for damage detection: II. Damage monitoring strategy,” Smart Material And Structure, Vol.16, pp. 260-274, 2007.
  14. [14] S. von Ende and R. Lammering, “Investigation on piezoelectrically induced Lamb wave generation and propagation,” Smart Material And Structure, Vol.16, pp. 1802-1809, 2007.
  15. [15] X. Wang, Y. Lu, and J. Tang, “Damage detection using piezoelectric transducers and the Lamb wave approach: 1 System analysis,” Smart Material And Structure, Vol.17, pp. 1-15, 2008 (025035).
  16. [16] Y. Lu, X. Wang, J. Tang, and Y. Ding, “Damage detection using piezoelectric transducers and the Lamb wave approach- II. Robust and quantitative decision making,” Smart Material And Structure, Vol.17, pp. 1-15, 2008 (025033).
  17. [17] B. C. Lee and W. J. Staszewski, “Sensor location studies for damage detection with Lamb waves,” Smart Material And Structure, Vol.16, pp. 399-408, 2007.
  18. [18] P. D. Wilcox, “Omni-Directional Guided Wave Transducer Array for the Rapid Inspection of Large Areas of Plate Structures,” IEEE Tran. Ultra. Ferr. and Freq. Cont., Vol.50, pp. 699-709, 2003.
  19. [19] A. C. Kak and M. Slaney, “Principles of Computerized Tomographic Imaging,” IEEE Press, 1999.
  20. [20] K. R. Leonard, E. V. Malyarenko, and M. K. Hinders, “Ultrasonic Lamb wave tomography,” Smart Material And Structure, Vol.18, pp. 1795-1808, 2002.
  21. [21] S. Khare, M. Razdan, N. Jain, P. Munshi, B.V. Soma Sekhar, and K. Balasubramaniam, “Lamb Wave Tomographic Reconstruction Using Various MART Algorithms,” Proc. National Seminar on Non-Destructive Evaluation. pp. 7-9, Dec. 2006.
  22. [22] Y. Lu, L. Ye, and Z. Su, “Crack identification in aluminum plates using Lamb wave signals of a PZT sensor network,” Smart Material And Structure, Vol.15, pp. 839-849, 2006.
  23. [23] P. S. Tua, S. T. Quek, and Q. Wang, “Detection of cracks in plates using piezo-actuated Lamb waves,” Smart Material and Structure, Vol.13, pp. 643-660 2007.
  24. [24] P. D. Wicox, C. Holmes, and B. W. Drinkwater, “Advanced Reflector Characterization with Ultrasonic Phased Arrays in NDE Application,” IEEE Trans. Ultra., Ferr. and Freq. Cont., Vol.54, pp. 1541-1550, 2007.
  25. [25] Y. Lu, L. Ye, Z. Su, and N. Huang, “Quantitative evaluation of crack orientation in aluminum plates based on Lamb waves,” Smart Material and Structure, Vol.16, pp. 1907-1914, 2007.
  26. [26] T. R. Hay, R. L. Royer, H. Gao, X. Zhao, and J. L. Rose, “A comparison of embedded sensor Lamb wave ultrasonic tomography approaches for material loss detection,” Smart Material And Structure, Vol.15, pp. 946-951, 2006.

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