Potential of Two Metaheuristic Optimization Tools for Damage Localization in Civil Structures
Publication: Journal of Aerospace Engineering
Volume 30, Issue 2
Abstract
In structural health monitoring, the presence of damage is detected and localized by outlining the differences between the initial state and current behavior of a given structure. The problem is often formulated as an optimization problem. In this paper, a highly nonlinear objective function that minimizes the discrepancies between the analytical and experimental features of a structure is introduced. Within a finite-element discretization, some stiffness parameters are chosen as reference variables. Two metaheuristic tools, the artificial bee colony (ABC) algorithm and the firefly algorithm (FA), are applied to proceed the iterations toward the global minima of the objective function. By comparing the identified and analytical stiffness matrices, the damage detection and localization are performed. These methods are applied to a steel structure. The efficiency of the two tools is compared.
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References
Betti, R., and Lin, J. W. (2004). “On-line identification and damage detection in non-linear structural systems using a variable forgetting factor approach.” Earthquake Eng. Struct. Dyn., 33(4), 419–444.
Camargo, M. P., Rueda, J. L., Erlic, I., and Añó, O. (2014). “Comparison of emerging metaheuristic algorithms for optimal hydrothermal system operation.” Swarm Evol. Comput., 18, 83–96.
Casciati, F., Elia, L., and Faravelli, L. (2014). “Optimization of sensors location and actuator control law.” 6WCSCM, 6th World Conf. on Structural Control and Monitoring, CIMNE 2014.
Casciati, S. (2008). “Stiffness identification and damage localization via differential evolution algorithms.” Struct. Control Health Monit., 15(3), 436–449.
Casciati, S. (2014). “Differential evolution approach to reliability-oriented optimal design.” Prob. Eng. Mech., 36, 72–80.
Casciati, S., and Elia, L. (2014a). “Potential of metaheuristic methods for damage localization and stiffness identification.” Proc., OPT-i, Int. Conf. on Engineering and Applied Sciences Optimization, Elsevier.
Casciati, S., and Elia, L. (2014b). “The potential of the firefly algorithm for damage localization and stiffness identification.” Recent Adv. Swarm Intell. Evol. Comput., 585, 163–178.
Casciati, S., and Elia, L. (2015). “Innovative, bio-inspired, metaheuristic methods targeted to SHM diagnostic goals.” Proc., 7SHMII–7th Int. Conf. on Structural Health Monitoring of Intelligent Structures, Techno-Press, Daejeon, Korea.
Degertekin, S. O., and Lamberti, L. (2013). “Comparison of hybrid metaheuristic algorithms for truss weight optimization.” Proc., 3rd Int. Conf. on Soft Computing Technology in Civil, Structural and Environmental Engineering, CSC 2013, Elsevier.
Elia, L. (2015). “Metaheuristic optimization tools for structural control.” Ph.D. thesis, Dept. of Civil Engineering and Architecture, Univ. of Pavia, Pavia, Italy.
Feltrin, G., Jalsan, K. E., and Flouri, K. (2013). “Vibration monitoring of a footbridge with a wireless sensor network.” J. Vibr. Control, 19(15), 2285–2300.
Gandomi, A. H., Yang, X.-S., and Alavi, A. H. (2011). “Mixed variable structural optimization using firefly algorithm.” Comput. Struct., 89(23–24), 2325–2336.
Goldberg, D. E. (1989). “Genetic algorithms in search.” Optimization and machine learning, Addison-Wesley, New York.
Guo, H. Y., Zhang, L., Zhang, L. L., and Zhou, J. X. (2004). “Optimal placement of sensors for structural health monitoring using improved genetic algorithms.” Smart Mater. Struct., 13(3), 528–534.
Hubbell, D., and Glisic, B. (2013). “Detection and characterization of early-age thermal cracks in high-performance concrete.” ACI Mater. J., 3(110), 323–330.
Kang, F., Li, J., and Li, J. (2013). “Artificial bee colony algorithm and pattern search hybridized for global optimization.” Appl. Soft Comput., 13(4), 1781–1791.
Kang, F., Li, J., and Xu, Q. (2009). “Structural inverse analysis by hybrid simplex artificial bee colony algorithms.” Comput. Struct., 87(13), 861–870.
Kang, F., Li, J., and Xu, Q. (2012). “Damage detection based on improved particle swarm optimization using vibration data.” Appl. Soft Comput., 12(8), 2329–2335.
Karaboga, D. (2005). “An idea based on honey bee swarm for numerical optimization.”, Erciyes Univ., Turkey.
Karaboga, D., and Basturk, B. (2008). “On the performance of artificial bee colony (ABC) algorithm.” Appl. Soft Comput., 8(1), 687–697.
Liao, T. W., Chang, P. C., Kuo, R. J., and Liao, C.-J. (2014). “A comparison of five hybrid metaheuristic algorithms for unrelated parallel-machine scheduling and inbound trucks sequencing in multi-door cross docking systems.” Appl. Soft Comput., 21, 180–193.
MATLAB 2014a [Computer software]. Natick, MA, MathWorks.
MSC Marc Mentat 2010 [Computer software]. MSC Software Corporation, Santa Ana, CA.
Nagarajaiah, S., and Basu, B. (2009). “Output only modal identification and structural damage detection using time frequency & wavelet techniques.” Earthquake Eng. Eng. Vibr., 8(4), 583–605.
Nair, K. K., Kiremidjian, A. S., and Law, K. H. (2006). “Time series-based damage detection and localization algorithm with application to the ASCE benchmark structure.” J. Sound Vibr., 291(1–2), 349–368.
Papadimitriou, C. (2004). “Optimal sensor placement methodology for parametric identification of structural systems.” J. Sound Vibr., 278(4), 923–947.
Song, Y. Z., et al. (2014). “Non-invasive damage detection in beams using marker extraction and wavelets.” Mech. Syst. Signal Process., 49(1–2), 13–23.
Sun, H., and Betti, R. (2014). “Simultaneous identification of structural parameters and dynamic input with incomplete output-only measurements.” Struct. Control. Health Monit., 21(6), 868–889.
Yang, X.-S. (2009). “Firefly algorithms for multimodal optimization.” Lect. Notes Comput. Sci., 5792, 169–178.
Yang, X.-S. (2010). Nature-inspired metaheuristic algorithms, 2nd Ed., Luniver Press, London.
Yao, Y., Tung, S. T. E., and Glisic, B. (2014). “Crack detection and characterization techniques-An overview.” Struct. Control Health Monit., 21(12), 1387–1413.
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© 2016 American Society of Civil Engineers.
History
Received: Mar 30, 2015
Accepted: May 26, 2016
Published online: Jul 25, 2016
Discussion open until: Dec 25, 2016
Published in print: Mar 1, 2017
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