journal article·2024-12

Unsupervised Machine Learning for Automatic Image Segmentation of Impact Damage in CFRP Composites

Olesya Zhupanska, Pavlo Krokhmal

Applied Composite Materials· Volume 31· Issue 6
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Abstract

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Research context

OpenAlex topics: Mechanical Behavior of Composites · Ultrasonics and Acoustic Wave Propagation · High-Velocity Impact and Material Behavior

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References (27)

Show source-provided references
1. Sierakowski, R.L., Newaz, G.M.: Damage Tolerance in Advanced Composites. Technomic Publishing Company, Inc., Lancaster, PA (1995)
2. Stock, S.R.: X-ray Micro Tomography of materials. Int. Mater. Rev. 44(4), 141–164 (1999)10.1179/095066099101528261 ↗
3. Schilling, P.J., Karedla, B.-P.R., Tatiparthi, A.K., Verges, M.A., Herrington, P.D.: X-ray computed Microtomography of Internal damage in Fiber Reinforced Polymer Matrix composites. Compos. Sci. Technol. 65, 2071–2078 (2005)10.1016/j.compscitech.2005.05.014 ↗
4. Tan, K.T., Watanabe, N., Iwahori, Y.: X-ray radiography and micro-computed tomography examination of damage characteristics in stitched composites subjected to impact loading. Compos. B. 42, 874–884 (2011)10.1016/j.compositesb.2011.01.011 ↗
5. Bull, D.J., Helfen, L., Sinclair, I., Spearing, S.M., Baumbach, T.: A comparison of multi-scale 3D X-ray Tomographic Inspection techniques for assessing Carbon Fibre Composite Impact damage. Compos. Sci. Technol. 75, 55–61 (2013)10.1016/j.compscitech.2012.12.006 ↗
6. Yu, B., Bradley, R.S., Soutis, C., Withers, P.J.: A comparison of different approaches for imaging cracks in composites by X-ray Microtomography. Philosophical Trans. Royal Soc. A. 374, 20160037 (2016)10.1098/rsta.2016.0037 ↗
7. Garcea, S.C., Wang, Y., Withers, P.J.: X-ray computed Tomography of Polymer composites. Compos. Sci. Technol. 156, 305–319 (2018)10.1016/j.compscitech.2017.10.023 ↗
8. Maire, E., Withers, P.J.: Quantitative X-ray tomography. Int. Mater. Rev. 59(1), 1–43 (2014)10.1179/1743280413Y.0000000023 ↗
9. Scott, A.E., Mavrogordato, M., Wright, P., Sinclair, I., Spearing, S.M.: In situ fibre fracture measurement in Carbon-Epoxy laminates using high resolution computed Tomography. Compos. Sci. Technol. 71, 1471–1477 (2011)10.1016/j.compscitech.2011.06.004 ↗
10. Leonard, F., Stein, J., Soutis, C., Withers, P.J.: The quantification of impact damage distribution in Composite laminates by Analysis of X-ray computed Tomograms. Compos. Sci. Technol. 152, 139–148 (2017)10.1016/j.compscitech.2017.08.034 ↗
11. Ellison, A., Kim, H.: Computed Tomography Informed Composite damage state Model Generation. J. Compos. Mater. 52, 3523–3538 (2018)10.1177/0021998318773464 ↗
12. Czabaj, M.W., Riccio, M.L., Whitacre, W.W.: Numerical Reconstruction of Graphite/Epoxy Composite Microstructure based on Sub-micron Resolution X-ray computed Tomography. Compos. Sci. Technol. 105, 174–182 (2014)10.1016/j.compscitech.2014.10.017 ↗
13. Kastner, J., Plank, B., Salaberger, D., Sekeljakastner, J.: Defect and Porosity Determination of Fibre Reinforced Polymers by X-ray Computed Tomography. In 2nd International Symposium on NDT in Aerospace, We.1.A.2. (2010)
14. Zhupanska, O.I., Krokhmal P.A.: Unsupervised Machine Learning Algorithms for Analysis of Low Velocity Impact Damage in Composite Structures from CT Image Data ASME International Mechanical Engineering Congress & Exposition, IMECE2022. (2022)10.1115/IMECE2022-96262 ↗
15. Goodfellow, I., Bengio, Y., Courville, A., Bengio, Y.: Deep Learning, Vol. 1. Cambridge: MIT Press. (2016)
16. Furat, O., Wang, M., Neumann, M., Petrich, L., Weber, M., Krill, C.E., Schmidt, V.: Machine Learning Techniques for the Segmentation of Tomographic Image Data of Functional Materials, Frontiers in Materials, 6, Article 145. (2019)10.3389/fmats.2019.00145 ↗
17. Berthod, M., Kato, Z., Yu, S., Zerubia, J.: Bayesian image classification using Markov Random fields. Image Vis. Comput. 14, 285–295 (1996)10.1016/0262-8856(95)01072-6 ↗
18. Iassonov, P., Gebrenegus, T., Tuller, M.: Segmentation of X-ray computed tomography images of porous materials: A crucial step for characterization and quantitative analysis of pore structures. Water Resour. Res. 45, W09415 (2009)10.1029/2009WR008087 ↗
19. Gong, Y., Shao, H., Luo, J., Li, Z.: A deep transfer learning model for inclusion defect detection of Aeronautics Composite materials. Compos. Struct. 252, 112681 (2020)10.1016/j.compstruct.2020.112681 ↗
20. Otsu, N.: A threshold selection method from Gray-Level Histograms. IEEE Trans. Syst. Man. Cybernetics. 9(1), 62–66 (1979)10.1109/TSMC.1979.4310076 ↗
21. Ridler, T.W., Calvard, S.: Picture thresholding using an iterative selection method. IEEE Trans. Syst. Man. Cybernetics. SMC–8, 630–632 (1978)
22. Kuo, H.H.: Gaussian Measures on Banach Spaces. Springer (1975)10.1007/BFb0082007 ↗
23. Kullback, S.: Information Theory and Statistics. Wiley (1959)
24. Rényi, A.: On Measures of Entropy and Information, In Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, 1: 547–561. (1961)
25. Ruszczynski, A.: Nonlinear Optimization. Princeton University Press. (2006)10.1515/9781400841059 ↗
26. Cui, Y., Pang, J.-S.: Modern Nonconvex Nondifferentiable Optimization, SIAM. (2021)10.1137/1.9781611976748 ↗
27. Demerath, B.M., Zhupanska, O.I.: Study of Low Velocity Impact Damage in CFRP Laminates using 3D Computed Tomography. In Proceedings of the American Society for Composites 30th Annual Technical Conference. (2015)