Abstract
The performance and behavior of composite structures can be significantly affected by degradation and damage. Degradation can be caused by exposure to environmental conditions and damage can be caused by handling conditions, such as impact and loading. Such damages are not always visible on the surface and could potentially lead to catastrophic structural failures. This paper addresses the specific challenge of using numerical simulations to assess damage detection techniques applied to composite laminated plates. This study aims to solve the direct and inverse problem of damage detection by combining numerical and experimental data. Finite element analysis was carried out to analyze the direct problem of mechanical response. Heuristic optimization techniques were used to solve the direct and inverse problem by combining data from a model with that of the experiment to identify structural damage. This study also sought to update the finite element model by minimizing the objective function. The structure studied was constituted of a composite plate. Two damage models were used: (i) circular hole and (ii) delamination (local stiffness reduction). The results of the optimization algorithms show good efficacy in the detection of structural damage, identifying the damaged location on the structure and also quantifying the size of the damage in real composite structures. A method has been proposed to identify the damage in CFRP plates using remote vibration measurements. Furthermore, the numerical simulation and experimental tests have been used to verify the method.
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References
Balageas D, Fritzen CP, Guemes A (2006) Structural health monitoring, vol 493. Wiley, Hoboken
Bayissa W, Haritos N (2007) Structural damage identification in plates using spectral strain energy analysis. J Sound Vib 307(1):226–249
Bledzki A, Kessler A, Rikards R, Chate A (1999) Determination of elastic constants of glass/epoxy unidirectional laminates by the vibration testing of plates. Compos Sci Technol 59(13):2015–2024
Boller C (2000) Next generation structural health monitoring and its integration into aircraft design. Int J Syst Sci 31(11):1333–1349
Chandrashekhar M, Ganguli R (2016) Damage assessment of composite plate structures with material and measurement uncertainty. Mech Syst Signal Process 75:75–93
Dos Santos JA, Soares CM, Soares CM, Pina H (2000) Development of a numerical model for the damage identification on composite plate structures. Compos Struct 48(1):59–65
Ewins DJ (1984) Modal testing: theory and practice, Vol. 15. Research studies press, Letchworth
Fan W, Qiao P (2011) Vibration-based damage identification methods: a review and comparative study. Struct Health Monit 10(1):83–111
Friswell M, Penny J, Garvey S (1998) A combined genetic and eigen sensitivity algorithm for the location of damage in structures. Comput Struct 69(5):547–556
Friswell MI (2008) Damage identification using inverse methods. Philos Trans R Soc Lond A Math, Phys Eng Sci 365(1851):393–410
Giurgiutiu V, Zagrai A (2005) Damage detection in thin plates and aerospace structures with the electro-mechanical impedance method. Struct Health Monit 4(2):99–118
Heslehurst RB (2014) Defects and damage in composite materials and structures. CRC Press, Baco Rotan
Hwang SF, He RS (2006) A hybrid real-parameter genetic algorithm for function optimization. Adv Eng Inform 20(1):7–21
Jafarkhani R, Masri SF (2011) Finite element model updating using evolutionary strategy for damage detection. Comput Aided Civ Infrastruct Eng 26(3):207–224
McCarthy C, McCarthy M, Lawlor V (2005) Progressive damage analysis of multi-bolt composite joints with variable bolt hole clearances. Compos B Eng 36(4):290–305
Meruane V, Heylen W (2010) Damage detection with parallel genetic algorithms and operational modes. Struct Health Monit 9(6):481–496
Michaels JE (2008) Detection, localization and characterization of damage in plates with an in situ array of spatially distributed ultrasonic sensors. Smart Mater Struct 17(3):035035
Mitchell M (1999) An introduction to genetic algorithms. MIT press, Cambridge
Morassi A, Vestroni F (2008) Dynamic methods for damage detection in structures. Springer Science & Business Media, Berlin
Mujica LE, Vehi J, Staszewski W, Worden K (2008) Impact damage detection in aircraft composites using knowledge-based reasoning. Struct Health Monit 7(3):215–230
Nanthakumar S, Lahmer T, Rabczuk T (2014) Detection of multiple flaws in piezoelectric structures using XFEM and level sets. Comput Methods Appl Mech Eng 275:98–112
Pawar PM, Ganguli R (2003) Genetic fuzzy system for damage detection in beams and helicopter rotor blades. Comput Methods Appl Mech Eng 192(16):2031–2057
Pinfold, M.K.: Composite mechanical properties for use in structural analysis. Ph.D. thesis, University of Warwick (1995)
Ragauskas P, Beleviˇcius R (2009) Identification of material properties of composite materials. Aviation 13(4):109–115
Rao SS, Yap FF (1995) Mechanical vibrations, vol 4. Addison-Wesley, New York
Rytter A (1993) Vibrational based inspection of civil engineering structures. Aalborg University, Aalborg
Seyedpoor S (2012) A two stage method for structural damage detection using a modal strain energy based index and particle swarm optimization. Int J Non-Linear Mech 47(1):1–8
Sinou JJ (2009) A review of damage detection and health monitoring of mechanical systems from changes in the measurement of linear and non-linear vibrations. In: Robert CS (ed) Mechanical vibrations: measurement, effects and control. Nova Science Publishers, pp 643–702. ISBN: 978-1-60692-037-4
Sohn H, Farrar CR, Hemez FM, Shunk DD, Stinemates DW, Nadler BR, Czarnecki JJ (2003) A review of structural health monitoring literature: 1996–2001. Los Alamos National Laboratory, USA
Srinivas V, Ramanjaneyulu K, Jeyasehar CA (2011) Multi-stage approach for structural damage identification using modal strain energy and evolutionary optimization techniques. Struct Health Monit 10(2):219–230
Stavroulakis G, Antes H (1998) Flaw identification in elastomechanics: BEM simulation with local and genetic optimization. Struct optim 16(2–3):162–175
Talreja R, Singh CV (2012) Damage and failure of composite materials. Cambridge University Press, Cambridge
Underhill P, Juurlink J, DuQuesnay D (2016) The use of safety cuts in fatigue damaged fastener hole repair. Int J Fatigue 91:242–247
Vo-Duy T, Ho-Huu V, Dang-Trung H, Nguyen-Thoi T (2016) A two-step approach for damage detection in laminated composite structures using modal strain energy method and an improved differential evolution algorithm. Compos Struct 147:42–53
Worden K, Dulieu-Barton J (2004) An overview of intelligent fault detection in systems and structures. Struct Health Monit 3(1):85–98
Worden K, Dulieu-Barton JM (2004) An overview of intelligent fault detection in systems and structures. Struct Health Monit 3(1):85–98
Yang XS (2010) Engineering optimization: an introduction with metaheuristic applications. Wiley, Hoboken
Yang ZB, Chen XF, Xie Y, Miao HH, Gao JJ, Qi KZ (2016) Hybrid two-step method of damage detection for plate-like structures. Struct Control Health Monit 23(2):267–285
Zhang T, Yan Y, Jin C (2016) Experimental and numerical investigations of honeycomb sandwich composite panels with open-hole damage and scarf repair subjected to compressive loads. J Adhes 92(5):380–401
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The authors would like to acknowledge the financial support from the Brazilian agency CNPq—Conselho Nacional de Desenvolvimento Científico e Tecnológico and CAPES—Coordenação de Aperfeiçoamento de Pessoal de Nível Superior.
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Gomes, G.F., Mendéz, Y.A.D., da Cunha, S.S. et al. A numerical–experimental study for structural damage detection in CFRP plates using remote vibration measurements. J Civil Struct Health Monit 8, 33–47 (2018). https://doi.org/10.1007/s13349-017-0254-3
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DOI: https://doi.org/10.1007/s13349-017-0254-3