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Tytuł artykułu

Skin-Spar Failure Detection of a Composite Winglet Using FBG Sensors

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Winglets are introduced into modern aircraft to reduce wing aerodynamic drag and to consequently optimize the fuel burn per mission. In order to be aerodynamically effective, these devices are installed at the wing tip section; this wing region is generally characterized by relevant oscillations induced by flights maneuvers and gust. The present work is focused on the validation of a continuous monitoring system based on fiber Bragg grating sensors and frequency domain analysis to detect physical condition of a skin-spar bonding failure in a composite winglet for in-service purposes. Optical fibers are used as deformation sensors. Short Time Fast Fourier Transform (STFT) analysis is applied to analyze the occurrence of structural response deviations on the base of strain data. Obtained results showed high accuracy in estimating static and dynamic deformations and great potentials in detecting structural failure occurrences.
Rocznik
Strony
287--300
Opis fizyczny
Bibliogr. 19 poz., fot., rys., tab.
Twórcy
autor
  • Italian Aerospace Research Center, CIRA Via Maiorise, 1, 81043 Capua, Italy
autor
  • University of Naples “Federico II”, Department of Industrial Engineering – Aerospace Division, Via Claudio, 21, 80125 Naples, Italy
  • NOVOTECH s.r.l. – Aerospace Advanced Technology, P.le D’Annunzio 15, 80125 Naples, Italy
autor
  • Italian Aerospace Research Center, CIRA Via Maiorise, 1, 81043 Capua, Italy
autor
  • University of Naples “Federico II”, Department of Industrial Engineering – Aerospace Division, Via Claudio, 21, 80125 Naples, Italy
Bibliografia
  • [1] K. Diamanti and C. Soutis. Structural health monitoring techniques for aircraft composite structures. Progress in Aerospace Sciences, 46(8):342–352, 2010. doi: 10.1016/j.paerosci.2010.05.001.
  • [2] C. Bockenheimer and H. Speckmann. Validation, verification and implementation of SHM at Airbus. In Proceedings of the 9th International Workshop on Structural Health Monitoring (IWSHM 2013), Stanford University, Stanford, CA, USA, pages 10–12, 2013.
  • [3] H. Speckmann and H. Roesner. Structual Health Monitoring: A contribution to the intelligent aircraft structure. In Proceedings of ECNDT 2006, 9th European Conference on NDT, Berlin, Germany, Sept. 2006.
  • [4] O. Shapira, S. Kedem, B. Glam, N.Y. Shemesh, A. Dvorjetski, N. Mashiach, J. Balter, R. Shklovsky, I. Sovran, N. Gorbatov, et al. Implementation of a fiber-optic sensing technology for global structural integrity monitoring of UAVs. In The 54th Israel Annual Conference on Aerospace Sciences, Tel-Aviv, Israel, 2014.
  • [5] R. De Oliveira, O. Frazão, J.L. Santos, and A.T. Marques. Optic fibre sensor for real-time damage detection in smart composite. Computers & Structures, 82(17):1315–1321, 2004. doi: 10.1016/j.compstruc.2004.03.028.
  • [6] E. Di Lorenzo, G. Petrone, S. Manzato, B. Peeters,W. Desmet, and F. Marulo. Damage detection in wind turbine blades by using operational modal analysis. Structural Health Monitoring, 15(3):289–301, 2016. doi: 10.1177/1475921716642748.
  • [7] I. Dimino and A. Calabrò. Structural damage identification by vibration parametres and fibre optic sensors. Czech Aerospace, 2009(3):33–41, 2009.
  • [8] S. Bhalla and C.K. Soh. Structural health monitoring by piezo-impedance transducers. I: Modeling. Journal of Aerospace Engineering, 17(4):154–165, 2004. doi: 10.1061/(ASCE)0893-1321(2004)17:4(154).
  • [9] S. Bhalla and C.K. Soh. Electromechanical impedance modeling for adhesively bonded piezotransducers. Journal of Intelligent Material Systems and Structures, 15(12):955–972, 2004. doi: 10.1177/1045389X04046309.
  • [10] A. De Fenza, A. Sorrentino, and P. Vitiello. Application of Artificial Neural Networks and Probability Ellipse methods for damage detection using Lamb waves. Composite Structures, 133:390–403, 2015. doi: 10.1016/j.compstruct.2015.07.089.
  • [11] R. Di Sante. Fibre optic sensors for structural health monitoring of aircraft composite structures: Recent advances and applications. Sensors, 15(8):18666–18713, 2015. doi: 10.3390/s150818666.
  • [12] H. Takeya, T. Ozaki, and N. Takeda. Structural health monitoring of advanced grid structure using multi-point FBG sensors. Proc. SPIE, 5762:204–211, 2005. doi: 10.1117/12.598759.
  • [13] H. Murayama, K. Kageyama, H. Naruse, A. Shimada, and K. Uzawa. Application of fiber-optic distributed sensors to health monitoring for full-scale composite structures. Journal of Intelligent Material Systems and Structures, 14(1):3–13, 2003. doi: 10.1177/1045389X03014001001.
  • [14] G. Fabbi, M. Ciminello, A. Mataloni, P. Perugini, A. Sorrentino, and A. Concilio. Filament wound solid rocket motor vessels strain measurement and potential Structural Health Monitoring through fiber optics. In The space Propulsion 201 Conference, Rome, Italy, 2-6 May 2016. Paper No. SP2016-3125185.
  • [15] M. Ciminello, I. Dimino, S. Ameduri, and A. Concilio. Fiber optic shape sensor for morphing wing trailing edge. In Proceedings of 26th International Conference on Adaptive Structures and Technologies (ICAST2015), pages 312–318, 14-16 Oct. 2015.
  • [16] J.R. Lee, C.Y. Ryu, B.Y. Koo, S.G. Kang, C.S. Hong, and C.G. Kim. In-flight health monitoring of a subscale wing using a fiber bragg grating sensor system. Smart Materials and Structures, 12(1):147, 2003. doi: 10.1088/0964-1726/12/1/317.
  • [17] A. De Fenza, G. Petrone, R. Pecora, and M. Barile. Post-impact damage detection on a winglet structure realized in composite material. Composite Structures, 169:129–137, 2017. doi: 10.1016/j.compstruct.2016.10.004.
  • [18] MD Nastran. Quick Reference Guide, 2011.
  • [19] K.O. Hill and G. Meltz. Fiber Bragg grating technology fundamentals and overview. Journal of Lightwave Technology, 15(8):1263–1276, 1997. doi: 10.1109/50.618320.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-64f28c3f-6675-4cfe-89d7-5f15c38d7b55
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