Ultrasonic C-Scan Image Processing Using Multilevel Thresholding for Damage Evaluation in Aircraft Vertical Stabilizer

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Author(s)

Angelika Wronkowicz 1,* Andrzej Katunina 1 Krzysztof Dragan 2

1. Institute of Fundamentals of Machinery Design, Silesian University of Technology, Gliwice, 44-100, Poland

2. Air Force Institute of Technology, Warsaw, 01-494, Poland

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2015.11.01

Received: 19 Jun. 2015 / Revised: 24 Jul. 2015 / Accepted: 8 Sep. 2015 / Published: 8 Oct. 2015

Index Terms

Ultrasonic testing, C-Scan image processing, damage evaluation, multilevel thresholding, composite structures, barely visible impact damage

Abstract

Following the "on condition maintenance" approach used for extending service life of an aircraft one of the major tasks is a nondestructive testing of its critical elements. Considering that many of elements of operated aircraft are manufactured from polymeric composites a special attention should be paid for diagnosing these elements due to their high vulnerability to barely visible impact damage. One of the primary testing techniques used for inspection of aircraft composite elements is an ultrasonic C-Scan technique which application results in planar images of emitted/received wave attenuation and a time of flight map. Due to the complex nature of barely visible impact damage occurrence it is difficult to analyze resulting C-Scan images. Therefore, using assistance based on image processing may help with "big–data" analysis of collected images. In this paper the authors proposed the image processing algorithm for semi-automatic evaluation of such damage distribution in aircraft composite structures. The algorithm is based on multilevel Otsu thresholding and morphological processing. Using the proposed algorithm an extraction of damage visualization from a C-Scan image as well as its characterization and 3D representation is possible. The developed approach will allow supporting diagnosing of composite structures with impact damage using C-Scan technique.

Cite This Paper

Angelika Wronkowicz, Andrzej Katunin, Krzysztof Dragan,"Ultrasonic C-Scan Image Processing Using Multilevel Thresholding for Damage Evaluation in Aircraft Vertical Stabilizer", IJIGSP, vol.7, no.11, pp.1-8, 2015. DOI: 10.5815/ijigsp.2015.11.01

Reference

[1]C.D. Rans, and R.C. Alderliesten, "Damage Tolerance Philosophy for Bonded Aircraft Structures", ICAF 2009, Bridging the Gap between Theory and Operational Practice, pp. 73–90, 2009 [25th Symposium of the International Committee on Aeronautical Fatigue, 2009].

[2]M.Y. Shiino, M.C.M. Faria, E.C. Botelho, and P.C. de Oliveira, "Assessment of cumulative damage by using ultrasonic C-Scan on carbon fiber/epoxy composites under thermal cycling," Mater. Res., vol. 15, pp. 495–499, 2012.

[3]A. Katunin, "Stone impact damage identification in composite plates using modal data and quincunx wavelet analysis," Arch. Civ. Mech. Eng., vol. 15, pp. 251–261, 2015.

[4]A. Katunin, K. Dragan, and M. Dziendzikowski, "Damage identification in aircraft composite structures: A case study using various non-destructive testing techniques," Compos. Struct., vol. 127, pp. 1–9, 2015.

[5]F. Tallavo, G. Cascante, and M. D. Pandey, "A novel methodology for condition assessment of wood poles usingultrasonic testing," NDT&E Int., vol. 52, pp. 149–156, 2012.

[6]G. Trtnik and M. Gams, "Recent advances of ultrasonic testing of cement based materials at early ages," Ultrasonics, vol. 54, pp. 66–75, 2014.

[7]G. Pascale and A. Lolli, "Crack assessment in marble sculptures using ultrasonic measurements: Laboratory tests and application on the statue of David by Michelangelo," J. Cult. Herit., in press.

[8]ó. Martín, M. Pereda, J.I. Santos, and J.M. Galán, "Assessment of resistance spot welding quality based on ultrasonic testing and tree-based techniques," J. Mater. Process. Tech., vol. 214, pp. 2478–2487, 2014.

[9]T. Watanabe, H.T.H. Trang, K. Harada, and C. Hashimoto, "Evaluation of corrosion-induced crack and rebar corrosion by ultrasonic testing", Constr. Build. Mater., vol. 67B, pp. 197–201, 2014.

[10]L. Bechou, Y. Ousten, B. Tregon, F. Marc, Y. Danto, R. Even, and P. Kertesz, "Ultrasonic images interpretation improvement for microassembling technologies characterization," Microelectron. Reliab., vol. 37, pp. 1787–1790, 1997.

[11]G. Corneloup, J. Moysan, and I.E. Magnin, "Bscan image segmentation by thresholding using coocurrence matrix analysis," Pattern Recogn., vol. 29, pp. 281–296, 1996.

[12]I. Cornwell, and A. McNab, "Towards automated interpretation of ultrasonic NDT data," NDT&E Int., vol. 32, pp. 101–107, 1999.

[13]C. Kotropoulos, X. Magnisalis, I. Pitas, and M.G. Strintzis, "Nonlinear ultrasonic image processing based on signal-adaptive filters and self-organizing neural networks," IEEE Trans. Image Process., vol. 3, pp. 65–77, 1994.

[14]E. Bozzi, G. Cavaccini, M. Chimenti, M. G. Di Bono, and O. Salvetti, "Defect detection in C-scan maps," S. Mach.Perc., vol. 17, pp. 545–553, 2007.

[15]A. Momtaz and A. Sadr, "Clustering of Ultrasonic C-Scan Images using Rosette Pattern," Int. J. Simul. – Syst. Sci. Tech., vol. 10, pp. 34–39, 2009.

[16]R. Rashli, E.A. Bakar, and A.R. Othman, "Feature analysis of ultrasonic C-Scan image for nondestructive evaluation," Proc. of the IIEEJ Image Electron. Vis. Comput. Workshop, Kuching, Malaysia, pp. 21–24, 2012.

[17]S. Ouadfel, and S. Meshoul, "A fully adaptive and hybrid method for image segmentation using multilevel thresholding," Int. J. Image Graph. Signal Process., vol. 5, pp. 46-57, 2013.

[18]T.M. Meksen, R. Drai, and F. Sellidj, "Pattern recognition in ultrasonic imagery using the Hough transform," Proc. of WCU, Paris, France, pp. 753–756, 2003.

[19]T.M. Meksen, B. Boudraa, and M. Boudraa, "A method to improve and automate flat defect detection during ultrasonic inspection," Int. J. Adapt. Control Signal Process., vol. 26, pp. 375–383, 2012.

[20]T.M. Meksen, M. Boudraa, and B. Boudraa, "Automatic detection of circular defects during ultrasonic inspection," Proc. of UKACC Int. Conf. on Control, Cardiff, UK, pp. 1003–1006, 2012.

[21]T.M. Meksen, M. Boudraa, and B. Boudraa, "Neural networks to select ultrasonic data in non destructive testing," Stud. Comput. Intell., vol. 489, pp. 205–210, 2013.

[22]S. Li, A. Poudel, and T.P. Chu, "Fuzzy logic based delamination detection in CFRP panels," Informatica, vol. 37, pp. 359–366, 2013.

[23]K. Dragan, M. Stefaniuk, and P. Synaszko, "Numerical approach for ultrasonic imaging of defects in composites," Compos. Theor. Pract., vol. 12, pp. 105–109, 2012.

[24]K. Dragan, M. Stefaniuk, A. Czulak, J. Bienia?, M. Dziendzikowski, A. Leski, M. Gude, and W. Hufenbach, "Automated data analysis based on signal processing for two dimensional NDI data of the composite structures," Przetwórstwo Tworzyw, vol. 19, pp. 4–8, 2013.

[25]M. Stefaniuk, and K. Dragan, "Preliminary approach for an NDT to FEM mapping software used for assessment of delamination-type damage," Proc. of 6th World Conf. Struct. Control Monit., Barcelona, Spain, pp. 2541–2551, 2014.

[26]K. Dragan, and S. Klimaszewski, "In-service flaw detection and quantification of the MiG-29 composite vertical tail skin," Proc. of European Conference of Non-Destructive Testing, Berlin, 2006.

[27]K. Dragan, and P. Synaszko, "In-service flaw detection and quantification in the composite structures of aircraft," Fatigue Aircraft Struct., vol. 1, pp. 37–41, 2009.

[28]N. Otsu, "A threshold selection method from gray-level histograms," IEEE Transactions on Systems, Man, and Cybernetics, vol. 9, pp. 62–66, 1979.