Amirkabir Journal of Civil Engineering

Amirkabir Journal of Civil Engineering

Estimation of Cracking, Yield, and Ultimate Capacity of FRP-Strengthened Reinforced Concrete and Steel Sections using Wavelet Transform

Document Type : Research Article

Authors
M.R. Mohammadizadeh
Saman Salami
Department of Civil Engineering, Technical & Engineering Faculty, university of Hormozgan, Bandar Abbas, Iran
10.22060/ceej.2020.17236.6499
Abstract
Damage detection is a topic of great importance for structural health monitoring. Many varieties of structural damage can be detected by examining changes in structural response in terms of stiffness. Wavelet transform is a powerful mathematical tool for the processing and time-frequency analysis of transient signals and has great potential to be used in structural damage detection. In FRP-strengthened reinforced concrete and steel sections, stiffness changes can be caused by cracking, yielding of steel components, crushing of concrete, or rupture of FRP panels. With the help of wavelet transform, it is possible to use the continuous measurements of the response to bend or torsional loading to estimate the capacity of the cross-section corresponding to the stiffness changes. In this paper, the bending of FRP-reinforced steel beams filled by concrete under bending and CFRP-reinforced concrete beams under pure torsion is evaluated. The results showed that the location of the damage appears as perturbations in the diagram of discrete wavelet coefficients, which indicate the time of cracking, yielding of steel, crushing of concrete in the compression zone, and rupture of FRP. Therefore, a wavelet transform-based data processing procedure can be used to estimate the cracking and yielding capacities of the beams subjected to torsion, the yielding capacity of the steel, and the ultimate capacity of the beams subjected to bending. The results demonstrated a high level of agreement between the estimates obtained from the discrete wavelet transform method and the examined experimental and numerical data.
Keywords
Wavelet transform
Damage detection
Cracking capacity
Torsion
Bending
Subjects
  1. Sumitro, Y. Matsui, M. Kono, T. Okamoto, K. Fujii, Long span bridge health monitoring system in Japan, Health Monitoring and Management Systems, Proceedings of SPIE 4337, (2001), 517–524.
  2. Cawley, R.D. Adams, The location of defects in structures from measurements natural frequencies, The Journal of Strain Analysis, 14(2), (1979), 49–57.
  3. J. joo, Damage Detection and System Identification using a Wavelet Energy Based Approach, (Doctoral dissertation, Columbia University), (2012).
  4. C. Su, T.Q. Le, C.S.  Huang, P.Y. Lin, Locating damaged storeys in a structure based on its identified modal parameters in Cauchy wavelet domain, Applied Mathematical Modelling, 53, (2017), 1–19.
  5. Zhong, S.O. Oyadiji, Detection of cracks in simply-supported beams by continuous wavelet transform of reconstructed modal data, Computers and Structures, 89(1-2), (2011), 127–148.
  6. Fan, P. Qiao, A 2-D continuous wavelet transform of mode shape data for damage detection of plate structures, International Journal of Solids and Structures, 46(25-26), (2009), 4379–4395.
  7. Yang, S.O. Oyadiji, Damage detection using modal frequency curve and squared residual wavelet coefficients-based damage indicator, Mechanical Systems and Signal Processing, 83, (2017), 385-405.
  8. S. Patel, A. P. Chourasia, S.K. Panigrahi, J. Parashar, N. Parvez, M. Kumar, Damage Identification of RC Structures using Wavelet Transformation, Procedia Engineering, 144, (2016), 336-342
  9. Wu, Q. Wang, Experimental studies on damage detection of beam structures with wavelet transform, International Journal of Engineering Science, 49, (2011), 253-261.
  10. Spagnoli,L. Montanari, B. Basu, B. Broderick, Nonlinear Damage Identification in Fiber-Reinforced Cracked Composite Beams through Time-Space Wavelet Analysis, Procedia Materials Science, 3, 2014, 1579-1584.
  11. Bagheri,S. Kourehli, Damage detection of structures under earthquake excitation using discrete wavelet analysis, Asian Journal of Civil Engineering (BHRC),14, 2013, 289-304.
  12. R. Mohammadizadeh, M.J. Fadaee, M. R. Ronagh, Improving Torsional Behavior of Reinforced Concrete Beams Strengthened with Carbon Fibre Reinforced Polymer Composite, Iranian Polymer Journal, 18, (2009), 315-327.
  13. W. AlZand, W.H.W. Badaruzzaman, A.A. Mutalib, A.H. Qahtan, Finite element analysis of square CFST beam strengthened by CFRP composite material, Thin-Walled Structures, 96, (2015), 348–358.
  14. Rucka, K. Wilde, Application of wavelet analysis in damage detection and localization. Wydaw, PG, (2007).
  15. Kumar,E. Foufoula‐Georgiou, Wavelet analysis for geophysical applications, Reviews of geophysics, 35, (1997), 385-412.
  16. Polikar, The wavelet tutorial, http://users.rowan.edu/~polikar/WAVELETS.
  17. J. Mallat, A theory of multiresolution signal decomposition: The wavelet representation, IEEE Transactions on Pattern Analysis & Machine Intelligence, 7, (1989).
  18. J. Mallat. Multiresolution approximation and wavelet orthonormal bases of L2(R), Transactions of the American mathematical society, 315(1), (1989).
  19. Misiti,Y. Misiti, G. Oppenheim,J. M. Poggi, Wavelet Toolbox User’s Guide, The Math Works Ins, First version, (1996), 2-36.
  20. Abaqus Analisys User’s Manual, Version 6.10, (2010).
  21. Omidi, V. Lotfi, Numerical Analysis of Cyclically Loaded Concrete under Large Tensile Strain by the Plastic-Damage Model, Sharif University of Technology, Scientia Iranica,17(3), (2010), 194-208.
  22. C. Sundarraja, G. Ganesh Prabhu, Finite element modelling of CFRP jacketed CFST members under flexural loading, Thin-Walled Struct, 49, (2011), 1483–1491.
Amirkabir Journal of Civil Engineering
Volume 53, Issue 5
August 2021
Pages 1937-1958