Tomographic reconstruction of isotropic materials using genetic algorithms with ultrasound time-of-flight projection data

Kodali, Shyam Prasad; Nageswara Rao, Boggarapu

doi:10.22061/jcarme.2020.4871.1596

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	Tomographic reconstruction of isotropic materials using genetic algorithms with ultrasound time-of-flight projection data
Journal of Computational & Applied Research in Mechanical Engineering (JCARME)
مقاله 18، دوره 11، شماره 1 - شماره پیاپی 21، مهر 2021، صفحه 227-242 اصل مقاله (1.13 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22061/jcarme.2020.4871.1596
نویسندگان
Shyam Prasad Kodali؛ Boggarapu Nageswara Rao^*
Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, A.P., India, 522502
تاریخ دریافت: 03 اسفند 1397، تاریخ بازنگری: 16 اردیبهشت 1399، تاریخ پذیرش: 20 اردیبهشت 1399
چکیده
Engineering materials and structures have crack-like defects leading to premature failures. The usage of fracture mechanics to assess the structural integrity requires knowledge on the type, location, shape, size, and orientation of the flaws. Tomographic reconstruction is one of the commonly used nondestructive testing methods for flaw characterization. The cross sectional image of the object being tested is obtained through the application of various reconstruction methods that are categorized as either analytical methods or iterative methods. In this work, an iterative algorithm that works on the principles of genetic algorithms is developed and used for the reconstruction. The results of simulation studies on the tomographic reconstructions using genetic algorithms for the identification of defects in isotropic materials are discussed in the paper. The solution methodology based on the use of genetic algorithms is applied to reconstruct the cross sections of test specimens with different flaw characteristics. Simulated time-of-flight data of ultrasound rays transmitted through the specimen under investigation is used as input to the algorithm. The time-of-flight data is simulated neglecting the bending of ultrasound rays and assuming straight ray paths. Numerical studies performed on several specimens with flaws of known materials but unknown location, size and shape are presented. The number of ultrasonic transmitters and receivers needed for complete scanning of the specimen’s cross section is analyzed and presented. The findings of the parametric analysis and sensitivity analysis in order to choose appropriate range of algorithm parameters for performance quality and robustness of the algorithm are presented. The performance of the present algorithm with noisy projection data is also discussed.
کلیدواژه‌ها
Non destructive evaluation؛ Tomography؛ Tomographic reconstruction؛ Genetic algorithms؛ Ultrasound time of flight

مراجع
[1] K.R. Leonard, E.V. Malyarenko, M.K. Hinders, “Ultrasonic Lamb wave tomography”, Inverse Probl., Vol. 18, No. 6, pp. 1795-1808, (2002). [2] P.P. Delsanto, A. Romano, M. Scalerandi, F. Moldoveanu, “Application of genetic algorithms to ultrasonic tomography”, J. Acoust. Soc. Am., Vol. 104, No. 3, pp. 1374–1381, (1998). [3] A. C. Kak and Malcolm Slaney, Principles of Computerized Tomographic Imaging, Society of Industrial and Applied Mathematics, (2001). [4] K. Bryant, R. Vaga, “Computer tomography from micro-electronics to assembled products”, Adv. Sci., Technol. Eng. Syst. J., Vol. 2, No. 3, pp. 932-936, (2017). [5] L. De Chiffre, S. Carmignato, J. P. Kruth, R. Schmitt, A. Weckenmann, “Industrial applications of computed tomography”, CIRP Annals, Vol. 63, No. 2, pp. 655-677, (2014). [6] X. Teng, R.E. Green Jr., “Ultrasonic tomographic imaging of defects in industrial materials”, Review of Progress in Quantitative Nondestructive Evaluation, Eds. D.O. Thompson, D.E. Chimenti, Plenum Press, New York, pp. 889-896, (1993). [7] P. Munshi, “A review of computerized tomography with application to two-phase flows”, Sadhana, Vol. 15, No. 1, pp. 43-55, (1990). [8] T. Ponikiewski, J. Katzer, “X-ray computed tomography of fibre reinforced self compacting concrete as a tool of assessing its flexural behavior”, Mater. Struct., Vol. 49, pp. 2131–2140, (2016). [9] S.J. Svärd, S. Holcombe, S. Grape, “Applicability of a set of tomographic reconstruction algorithms for quantitative SPECT on irradiated nuclear fuel assemblies”, Nucl. Instrum. Methods Phys. Res., Sect. A, Vol. 783, pp. 128-141, (2015). [10] J.F. Greenleaf, “Computerized tomography with ultrasound”, Proc. IEEE, Vol. 71, No. 3, pp. 330–337, (1983). [11] B. Jiang, W. Zhao, W. Wang, “Improved ultrasonic computerized tomography method for STS (steel tube slab) structure based on compressive sampling algorithm”, Appl. Sci. Vol. 7, No. 5, pp. 432, (2017). [12] J.L. Rose, “A baseline and vision of ultrasonic guided wave inspection potential”, J. Press. Vessel Tech., Vol. 124, No. 3, pp. 273–282, (2002). [13] C. Byrne, “Iterative algorithms in tomography”, (2005). [14] R.M. Lewitt, “Reconstruction algorithms: transform methods”, Proc. IEEE, Vol. 71, No. 3, pp. 390–408, (1983). [15] Y. Censor, “Finite series-expansion reconstruction methods”, Proc. IEEE, Vol. 71, No. 3, pp. 409–419, (1983). [16] E.F. Oliveira, S.B. Melo, C.C. Dantas, D.A. A. Vasconcelos, L.F. Cadiz, “Comparison among tomographic reconstruction algorithms with a limited data”, Proc. Int. Nucl. Atlantic Conf. - INAC 2011, ISBN: 978-85-99141-04-5 (2011). [17] N.N. Kishore, P. Munshi, M.A. Ranamale, V.V. Ramakrishna, W. Arnold , “Tomographic reconstruction of defects in composite plates using genetic algorithms with cluster analysis”, Res. Nondestr. Eval., Vol. 22, No. 1, pp. 31-60, (2011). [18] K. Deb, Optimization for Engineering Design: Algorithms and Examples, Prentice Hall of India, New Delhi, (2004). [19] R.S. Bichkar, A.K. Ray, “Tomographic reconstruction of circular and elliptical objects using genetic algorithm”, IEEE Signal Process. Let., Vol. 5, pp. 248–251, (1998). [20] K. J. Batenburg, “An evolutionary algorithm for discrete tomography”, Discrete Appl. Math., Vol. 151, pp. 36 – 54, (2005). [21] C. Valenti, “A genetic algorithm for discrete tomography reconstruction”, Genet. Program. Evolvable Mach., Vol. 9, No. 1, pp. 85–96, (2008). [22] X. Yang, J.R. Ommen, R.F. Mudde, “Comparison of genetic algorithm and algebraic reconstruction for X-ray tomography in bubbling fluidized beds”, Powder Technol., Vol. 253, pp. 626-637, (2014). [23] T. Weise, “Global Optimization Algorithms-Theory and Application”, Version: 2009-06-26.
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Tomographic reconstruction of isotropic materials using genetic algorithms with ultrasound time-of-flight projection data