Automatic Identification of Crack in Ultrasonic Infrared Imaging

Article Preview

Abstract:

Ultrasonic Infrared Imaging is a novel NDE technique, which performs well on material internal defect detection, such as metal fatigue crack, composite material impact damage and adhesion and so on. Traditional defect identification often depends on eyes and professional experience, which can’t give a clear conclusion of defect information. The identification algorithm based on time sequence images is low-level. Therefore, taking the crack detection in Ultrasonic IR Imaging as an example, after contrastive analysis of shape characters and gray distribution between crack region and normal region, characteristic parameters for different regions was creatively extracted in this paper. An automatic recognition algorithm based on Weighted Support Vector Machines is put forward for crack recognition. Subsequently, the correctness of the algorithm was validated by experiments.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 605-607)

Pages:

1001-1006

Citation:

Online since:

December 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Shuyi. Zhang. Ultrasonic infrared thermography and its applications in nondestructive evaluation[J]. Applied Acoustics,2004, 12(5):1-6.(In Chinese)

Google Scholar

[2] J. Renshaw, J. C. Chen, S. D. Holland, et al. The Sources of Heat Generation in Vibrothermography[J]. NDT&E International , 2011, 44:736–739.

DOI: 10.1016/j.ndteint.2011.07.012

Google Scholar

[3] Hui Liu, Junyan Liu, Yang Wang. Detection of contacting interface-type defects using ultrasound lock-in thermography [J]. Optics and Precision Engineering,2010,18(3): 653-661. (In Chinese)

Google Scholar

[4] X. Han, Z. Zeng, W. Li, et al. Acoustic chaos for enhanced detectability of cracks by sonic infrared imaging [J]. J. Appl. Phys., 2004, 95(7):3792-3797.

DOI: 10.1063/1.1652243

Google Scholar

[5] R. L. Thomas, X. Han, L. D. Favro, et al. Infrared Imaging of Defects in Materials with Chaotic Sonic Excitation[C]. International Ultrasonics Symposium Proc., 2010: 591-594.

DOI: 10.1109/ultsym.2010.5935448

Google Scholar

[6] S. M. Shepard, T. Ahmed, J. R. Lhota. Experimental Considerationsin Vibrothermography [C]. Proc. SPIE. 2004, SPIE-5405: 332-335.

Google Scholar