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Damage Detection of Steel-Concrete Composite Beam

REFERENCES 1. Uhl T.: Mechatronics In Diagnostics ; Diagnostyka, 3(47), Publisher 2008, 143-152. 2. Rucka M.: Neuro-Wavelet damage detection technique in beam, plate andshell structures with experimental validation , Journal of Theoretical and Applied Mechanics 48, 3 (2010) 579-604. 3. Białasiewicz J. T.: Falki I aproksymacje ; Wydawnictwo Naukowo-Techniczne, ISBN 83-204-2971-4, Warszawa, Publisher 2004. 4. Doebling S., Farrar, C., Prime, M., and Shevits, D.: Damage identification and health monitoring of structural and mechanical

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Damage detection in stiffened plates by wavelet transform

-102. Rucka, M. Wilde, K., 2006. Application of continuous wavelet transform in vibration based damage detection method for beams and plates. Journal of Sound and Vibration, 297, pp.536-550. Surace, C. Ruotolo, R., 1994. Crack Detection of a Beam Using the Wavelet Transform. Proc. of the 12th International Modal Analysis Conference, Honolulu, pp.1141-1147. Wang, W.J. McFadden, P.D., 1996. Application of Orthogonal Wavelets to Early Gear Damage Detection. Mechanical Systems and Signal Processing, 9, pp.497-508. Yang, J.M. Hwang

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Damage Detection of A T-Shaped Panel by Wave Propagation Analysis in the Plane Stress / Wykrywanie Uszkodzen W Tarczy Typu T Z Uzyciem Analizy Propagacji Fal W Płaskim Stanie Naprezenia

pseudospectral finite element method. International Journal of Solids and Structures 43, 4997-5031, 2006. 7. P. Kudela, M. Krawczuk, W. Ostachowicz, Wave propagation modelling in 1D structures using spectral finite elements. Journal of Sound and Vibration, 300, 88-100, 2007. 8. J. Chróścielewski, M. Rucka, K. Wilde, W. Witkowski, Formulation of spectral truss element for guided waves damage detection in spatial steel trusses. Archives of Civil Engineering 55(1), 43-63, 2009. 9. W. Witkowski, M. Rucka, K. Wilde, J. Chróścielewski

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Damage detection in composite laminates aeronautics structures through accelerometers network

for composite structures using visualized Lamb-wave propagation, Composites Science and Technology 67, 3202-3208, 2007. H. Boukabache, S. Ksouri, C. Escriba, J.Y. Fourniols, Piezoelectric sensor/actuator network for SHM and damage detection on Airplane Door, Asia-Pacific Workshop on Structural Health Monitoring, Tokyo, Japan, 2010 C. Escriba, H. Boukabache, S. Ksouri, M. Lastapis, T. Camps, J.M. Dilhac, S. Rolet, J.Y. Fourniols, Sensor Network for non destructive control of aeronautics structures: piezo or

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Application Of Guided Wave Propagation In Diagnostics Of Steel Bridge Components

Research 104, 81–90, 2015 5. M. Piekarczyk, R. Grec, Application of adhesive bonding in steel and aluminium structures, Archives of Civil Engineering, 58, 309–329, 2012 6. M. Rucka, Wave Propagation in Structures. Modelling, Experimental Studies and Application to Damage Detection, Wydawnictwo Politechniki Gdańskiej, Gdańsk 2011 7. M. Rucka, Modelling of in-plane wave propagation in a plate using spectral element method and Kane-Mindlin theory with application to damage detection. Archive of Applied Mechanics 81, 1877–1888, 2011 8. M. Rucka, W

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Development of an on-Line Damage Detection, Discrimination and Tracking System for the Spin Rig Facility

., Chen, W. R., Wu, X. J., Residual life assessment of a critical component of a gas turbine–achievements and challenges , Paper GT2014-26423, ASME Turbo Expo 2014, Düsseldorf, Germany 2014. [6] Brockman, R. A., Huelsman, M., John, R., Simulation of Deformation Modes for Damage Detection in Turbine Engine Disks, Materials Damage Prognosis , J. M. Larsen et al. (ed.), TMS, pp. 197-201, 2005. [7] Butz, M. G., Rodriquez, H. M., Propulsion Health Monitoring for Enhanced Safety , NASA Report, NASA/CR-2003-212291, 2003. [8] Chana, K., Sridhar, V., Sigh, D

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An Approach to Damage Detection in the Aircraft Structure with the Use of Integrated Sensors – The Symost Project

piezosensor array for damage localization. Struct. Health Monit . Vol. 2(2), p. 137. [16] Mustapha F., Worden K., Pierce S.G. & Manson G. (2007). Damage detection using stress waves and multivariate statistics: an experimental case study of an aircraft component. Strain , Vol. 43(1), p. 47. [17] Trendafilova, I., Cartmell, M.P. and Ostachowicz, W. (2008). Vibration-based damage detection in an aircraft wing scaled model using principal component analysis and pattern recognition. J. Sound Vib . Vol. 313(3), p. 560. [18

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Damage Detection of Concrete Gravity Dams using Hilbert-Huang Method

References A.Farsayi, R.Abbasnia. 2010. “Wavelet Transform in Damage Detection of Structures.” 6th Conference of Iranian civil engineering . Aldemir, Alper et al. 2015. “Pseudo-Dynamic Testing of a Concrete Gravity Dam.” Alembagheri, Mohammad, and Mohsen Ghaemian. 2013. “Damage Assessment of a Concrete Arch Dam through Nonlinear Incremental Dynamic Analysis.” Soil Dynamics and Earthquake Engineering 44: 127–37. http://dx.doi.org/10.1016/j.soildyn.2012.09.010 Allen, J B. 1977. “Short Term Spectral Analysis, Synthesis, and Modification

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SHM Supporting Damage Tolerance Design Philosophy As a Challenge for Designers of Future Airframes

College of Science Technology and Medicine, September 2000. Kessler, S. S., Spearing, S. M., Soutis, C.: Optimization of Lamb Wave Methods for Damage Detection in Composite Materials. Technology Laboratory for Advanced Composites Department of Aeronautics and Astronautics Massachusetts Institute of Technology, SHM-2001. Chien, Y. H.: A LISP-Based Expert System for Detecting Failures in Aircraft Systems. 1984. Pidaparti, R. M.: Aircraft Structural Integrity Assessment through Computational

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Choice of Appropriate Control Values for Effective Analyses of Damage Detection

Abstract

The article is devoted to a suitable choice of input parameters for the efficient running of a self-developed code used for damage detection. The code was prepared in Office Excel VBA, which used a non-destructive vibration-based method. The primary aim of the code is to determine the change in bending stiffness by using the FE model updating method, and the aim of the paper is to determine the effect of the input data on the bending stiffness calculations. The code was applied for a numerical model of a steel bar. The steel bar was a simply supported beam with a span of 3.5 m. The time of the calculations and precision of the identification were investigated. The values of the time consumption depend on the input values, the desired limit of the accepted error, and the length of the step in every iteration. Data from an experimental model was analysed. The model was made of wooden and plaster boards. The calculations were done in accordance with suitable input data from a parametric study.

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