Abstract
The identification of those differences between the current behavior and the initial state of a structure which are indicative of the presence of damage is one of the aims of structural health monitoring. Since the last decades, considerable research advances have been conducted in the optimization field. In this paper, an objective function that minimizes the discrepancies between the analytical and the experimental modal features obtained from the measurements of the actual dynamic response of a structure is formulated. Once the stiffness parameters are set as design variables, the firefly algorithm is applied to carry out the iterations toward the global minima. Partial solutions are analyzed along different steps of the procedure and identified as local optima by calculating the new stiffness matrices and estimating the corresponding values of the objective function. Eventually, the damage detection and localization are pursued by the comparison between the stiffness matrix identified once the optimization process is finished and the starting one. This procedure is applied to a numerical example, which is representative of a generic structure meshed into finite elements where damage is introduced as a local stiffness reduction.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Gandomi, A.H., Yang, X.S., Alavi, A.H.: Mixed variable structural optimization using firefly algorithm. Comput. Struct. 89, 2336–2535 (2011)
Perera, R., Ruiz, A., Manzano, C.: An evolutionary multiobjective framework for structural damage localization and quantification. Eng. Struct. 292, 2540–2550 (2007)
Yang, X.S.: Nature-inspired metaheuristic algorithms, 2nd edn. Luniver Press (2010)
Yang, X.S.: Multiobjective firefly algorithm for continuous optimization. Eng. Comput. 29, 175–184 (2013)
Yang, X.S.: Firefly algorithms for multimodal optimization, in stochastic algorithms: foundations and applications, SAGA 2009. Lect. Notes Comput. Sci. 5792, 169–178 (2009)
Casciati, F., Elia, L., Faravelli, L.: Optimization of sensors location for structural monitoring, on the proceedings of OPT-i, international conference on engineering and applied sciences optimization. Kos Island, Greece, (2014)
Casciati, S., Elia, L.: Potential of metaheuristic methods for damage localization and stiffness identification, on the proceedings of OPT-i, international conference on engineering and applied sciences optimization. Kos Island, Greece (2014)
Casciati, S.: Stiffness identification and damage localization via differential evolution algorithms. Struct. Control Health Monit. 15, 439–449 (2008)
Matlab Matlab user manual. Mathworks Inc., Lowell (2013)
Nair, K.K., Kiremidjian, A.S., Law, K.H.: Time series-based damage detection and localization algorithm with application to the ASCE benchmark structure. J. Sound Vib. 291, 349–368 (2006)
Papadimitriou, C.: Optimal sensor placement methodology for parametric identification of structural systems. J. Sound Vib. 278, 923–947 (2004)
Morlier J.: Méthodes d’analyse des déformées modales par traitement du signal pour le diagnostic in situ de structures. Ph.D. Thesis, University of Bordeaux, France (2005) (in French)
El-Borgi, S., Choura, S., Ventura, C., Baccouc, M., Cherif, F.: Modal identification and model updating of a reinforcement concrete bridge. Smart Struct. Syst. 1, 83–101 (2005)
Savoia M., Vincenzi L.: Differential evolution algorithm for dynamic structural identification. In: Proceedings of ICOSSAR’05, Rome, Italy, Millpress, Rotterdam (2005)
S. Casciati, L. Faravelli, Stiffness matrix estimation via differential evolution algorithm. In: Proceedings of the Third European Workshop on Structural Health Monitoring, Granada, Spain. DEStech Publications, Lancaster, U.S.A. (2006)
Faravelli, L., Marazzi F.: Stiffness matrices and genetic algorithm identifiers toward damage detection. In: Proceedings of IABMAS’06, Porto, Portugal (2006)
Acknowledgments
The authors gratefully acknowledge the financial support provided by the corresponding Athenaeum Research Grants.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Casciati, S., Elia, L. (2015). The Potential of the Firefly Algorithm for Damage Localization and Stiffness Identification. In: Yang, XS. (eds) Recent Advances in Swarm Intelligence and Evolutionary Computation. Studies in Computational Intelligence, vol 585. Springer, Cham. https://doi.org/10.1007/978-3-319-13826-8_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-13826-8_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13825-1
Online ISBN: 978-3-319-13826-8
eBook Packages: EngineeringEngineering (R0)