An Image Enhancement Technique for Ultrasonic NDE of CFRP Panels

This paper discusses an image enhancement technique based on a standard deviation method to obtain high contrast C-scan results by using immersion ultrasonic testing. Ultrasonic C-scan results have relatively low resolution and poor imaging quality in anisotropic composites due to the speckle noise produced by the interference of backscattered signals. This developed technique will aid nondestructive evaluation (NDE) inspectors in making quick, accurate, and reliable decisions. A high quality region of interest (ROI) image was first reconstructed from the raw amplitude data obtained from ultrasonic testing. Then, a standard deviation-based method was applied on ROI images to improve the edge contrast of the defect area to the nondefect area. The results obtained demonstrated that this applied method can greatly improve the image quality and offer detailed information of defects in an ROI by restraining the noises effectively. We believe this technique can make the defect evaluation process much easier and more accurate, and it can be expected to be a novel method for the ultrasonic C-scan result enhancement.

1. Sihn, S., R.Y. Kim, K. Kawabe and S.W. Tsai. “Experimental studies of thin-ply laminated composites,” Composites Science and Technology, 64 (6) 996-1008, 2007. 2. Graham, D., P. Maas, G.B. Donaldson and C. Carr. “Impact damage detection in carbon fiber composites using HTS SQUIDs and neural networks,” NDT&E International 37, 565-570, 2004. 3. Chu, T.C., A. Leyte, A. DiGregorio, S. Russell and J.L. Walker. “Micro-Cracking Detection in Laminated Composites,” Proc. of ASNT Spring Conference and 11th Annual Research Symposium, Portland, OR, 2002. 4. Im, K.H., D.K. Hsu, I.Y. Yang. “Inspection of Inhomogeneities in Carbon/Phenolic Matrix Composite Materials Using NDE Techniques,” Key Engineering Materials. Volumes 270–273, pp. 1799-1805, 2004. 5. Lee, J.H., S.W. Choi, K.S. Kim, J.H. Park and J.H. Byun, “Nondestructive Characterisation of Carbon/Carbon Brake Disks Using Ultrasonics,”, 2001. 6. Ruosi, A., “Nondestructive detection of damage in carbon fiber composite,” Journal of Physical stat., Volume 2 (5), pp. 1153-1155, March 2005. 7. Bray, D.E. and D. McBride. Nondestructive testing techniques, Wiley-Interscience Publication, John Wiley & Sons, Inc., New York, 1992. 8. Liu, N., Q.M. Zhu, C.Y. Wei, N.D. Dykes and P.E. Irving. “Impact damage detection in carbon fiber composites using neural network and acoustic emission,” Key Eng Mater,167-168: 45-54, 1999. 9. Zennouhi, R. and Lh. Masmoudi, “IEEE Xplore - Image segmentation using hierarchical analysis of 2D-histograms - Application to medical images,” Proc. of Multimedia Computing and Systems International Conference, (s): pp. 480- 483, Ouarzazate, 2009. 10. Gonzalez, R.C. and R.E. Woods. Digital Image Processing, 3rd ed., Prentice Hall, Upper Saddle River, NJ, 2008. 11. Poudel, A., S. Li, T.C. Chu, D. Palmer and R. Engelbart. “An Intelligent Systems Approach for Detecting Delamination Defects due to Impact Damage in CFRP Panel by Using Ultrasonic Testing,” Proc. of ASNT Fall Conference and 21st Annual Research Symposium, Palm Springs, CA, Oct. 2011. 12. Poudel, A., S. Li, T.C. Chu, D. Palmer and R. Engelbart. “Neural-Fuzzy Approach in Detecting and Classifying Foreign Object Inclusions in CFRP Panel by Using Ultrasonic Testing,” Proc. of ASNT Fall Conference and 21st Annual Research Symposium, Palm Springs, CA, Oct. 2011. 13. Chen, S. and D. Li. “Image binarization focusing on objects,” Neurocomputing, 69 (2006), 2411–2415. 14. Lee, J. “Digital Image Enhancement and Noise Filtering by Use of Local Statistics,” IEEE Trans. Pattern Anal. Mach. Intell, Volume 2, Issue 2, February 1980. 15. Huang, J.S. and D.H. Tseng. “Statistical theory of edge detection,” Comput. Vision Graphics Image Process, Volume 43, pp. 337-346, 1988. 16. Marr, D. and E. Hidreth. “Theory of edge detection,” Proc. Royal Soc. London PAMI-6, pp. 58. 1984. 17. Haralic, R.M. “Digital step edges from zero crossing second directional derivatives,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-6, pp. 58-68, 1984. 18. Torre, V. and T. Poggio. “On detecting edges,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-2, pp. 147-163, 1986. 19. Canny, J. “A computational approach to edge detection,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-8, pp. 679-698, 1986. 20. Shyr, T.W. and Y.H. Pan. “Impact resistance and damage characteristics of composite laminates,” Composite Structures, Volume 62, No. 2, pp. 193-203, Nov. 2003
Usage Shares
Total Views
25 Page Views
Total Shares
0 Tweets
0 PDF Downloads
0 Facebook Shares
Total Usage