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Structural damage detection using non-classical vibro-acoustic approaches

Treść / Zawartość
Identyfikatory
Warianty tytułu
Konferencja
Symposium Vibrations In Physical Systems (27 ; 09-13.05.2016 ; Będlewo koło Poznania ; Polska)
Języki publikacji
EN
Abstrakty
EN
The paper demonstrates how non-classical approaches can be used for structural health monitoring. Wavelet-based modal analysis, various non-classical nonlinear acoustic techniques and cointegration are used for damage detection. These approaches are illustrated using various examples of damage detection in metallic and composites structures.
Rocznik
Tom
Strony
13--24
Opis fizyczny
Bibliogr. 16 poz., il. kolor., fot., wykr.
Twórcy
  • Department of Robotics and Mechatronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow
  • Department of Robotics and Mechatronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow
autor
  • Department of Robotics and Mechatronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow
autor
  • Department of Robotics and Mechatronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow
autor
  • Department of Robotics and Mechatronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow
  • Department of Robotics and Mechatronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow
Bibliografia
  • 1. A. G. Poulimenos, S. D. Fassois, Parametric time-domain methods for non-stationary random vibration modelling and analysis - A critical survey and comparison. Mechanical Systems and Signal Processing, 20 (2006) 763 – 816.
  • 2. P. Orlowski, Selected problems of frequency analysis for time varying, discrete-time systems using singular value decomposition and discrete Fourier transform, J. of Sound and Vibration, 278(4-5) (2009) 903 – 921.
  • 3. B. Basu, S. Nagarajaiah, A. Chakraborty, Online identification of linear time-varying stiffness of structural systems by wavelet analysis, Structural Health Monitoring, 7(1) (2008) 21 – 36.
  • 4. W. J. Staszewski, D.M. Wallace, Wavelet-based Frequency Response Function for time-variant systems - an exploratory study, Mechanical Systems and Signal Processing, 47 (2014) 35 – 49.
  • 5. R. S. Pathak, The Wavelet Transform, Atlantis Press/World Scientific Paris 2009.
  • 6. K. Dziedziech, W. J. Staszewski, T. Uhl, Wavelet-based modal analysis for time-variant systems, Mechanical Systems and Signal Processing, 50-51 (2015) 323 – 337.
  • 7. K. Dziedziech, W. J. Staszewski, B. Basu, T. Uhl, Wavelet-based detection of abrupt changes in natural frequencies of time-variant systems, Mechanical Systems and Signal Processing, 64-65 (2015) 347 – 359.
  • 8. D. Broda, W. J. Staszewski, A. Martowicz, T. Uhl, V. Silberschmidt, Modelling of nonlinear crack-wave interactions based on ultrasound – a review, J. of Sound and Vibration, 333(4) (2014) 1097 – 1118.
  • 9. D. Donskoy, A. Sutin, A. Ekimov, Nonlinear acoustic interaction on contact interfaces and its use for nondestructive testing, NDT&E International, 34 (2001) 231 – 238.
  • 10. Z. Parsons, W. J. Staszewski, Nonlinear acoustics with low-profile piezoceramic excitation for crack detection in metallic structures, Smart Materials and Structures, 15 (2006) 1110 – 1118.
  • 11. A. Klepka, W. J. Staszewski, R. B. Jenal, M. Szwedo, J. Iwaniec, T. Uhl, Nonlinear acoustics for fatigue crack detection – Experimental investigations of vibro – acoustic wave modulations, Structural Health Monitoring, 11 (2012) 197 – 211.
  • 12. L. Pieczonka, L. Zietek, A. Klepka, W. J. Staszewski, F. Aymerich, T. Uhl, Impact damage imaging in composites using nonlinear vibro-acoustic wave modulations, submitted to Structural Control and Health Monitoring.
  • 13. K. Dziedziech, L. Pieczonka, P. Kijanka, W. J. Staszewski, Enhanced nonlinear crcak-wave interactions for structural damage detection based on guided ultrasonic waves, Structural Control and Health Monitoring, (2016), available online before print DOI: 10.1002/stc.1828.
  • 14. R. F. Engle, C. W. J. Granger, Cointegration and error-correction: representation, estimation and testing, Econometrica, 55 (1987) 251 – 276.
  • 15. E. J. Cross, K. Worden, Q. Chen, Cointegration: A novel approach for the removal of environmental trends in structural health monitoring data, Proc. R. Soc. A 467, (2011) 2712 – 2732.
  • 16. P. B. Dao, W. J. Staszewski, Lamb wave based structural damage detection using cointegration and fractal signal processing, Mechanical Systems and Signal Processing, 49 (2014) 285 – 301.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8d952777-7281-4ad8-9e4d-e6333311a28d
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