International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

D. Mallikarjuna Reddya,* and S. Swarnamani b

Mechanical Engineer, Chennai-73, India
Mechanical Engineering Department, Indian Institute of Technology Madras, Chennai-36, India


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ABSTRACT


The objective of current work is to show the effectiveness of using wavelet transform for detection and localization of small damages. The spatial data used here are the mode shapes and strain energy data of the damaged plate. Because the wavelet coefficients are performed with various scale indices, local perturbations in the mode shapes and strain energy data can be found in the finer scale that are positioned at the locations of the perturbations. The continuous wavelet transform (CWT) using complex Gaussian wavelet with four vanishing moments is used to get the spatially distributed wavelet coefficients so as to identify the damage position on a square plate. The mode shape and strain energy data of the square plate with damage of different sizes are obtained by using ANSYS 9.0. The damage is simulated by reducing the thickness of one element out of 625 elements used for modeling. It is observed that by using modal data as input, damage can be identified if the reduction in thickness in one of the elements is at least 10%. Use of strain energy data as input to the wavelet analysis provides detection up to less than 10% damage. Lipschtiz (Hoelder) exponent (α) and Intensity factor (K) is derived from the coefficients to quantify the relation between damage and change in wavelet coefficients derived from modal and elemental strain energy data. The variation of maximum absolute wavelet coefficients versus percentage of damage for different mode shapes and scales are studied Influence of boundary conditions of the plate on damage identification has been studied, especially for damage near boundaries. Another objective of this paper is to apply wavelet transform to highlight the detection and localization of damage in beam and stiffened panel using experimental modal data as input to the wavelet analysis.  This in real time has potential to be used in structural damage monitoring.


Keywords: Structural health monitoring; damage detection; modal analysis; spatial wavelets; lipschitz (hoelder) exponent.


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REFERENCES


  1. [1] Liew, K. W. and Wang, Q. 1998. Application of wavelet theory for crack Identification in structures. Journal of Engineering Mechanics, 124: 152-157.

  2. [2] Wang, Q. and Deng. X. 1999. Damage detection with spatial wavelets. International Journal of Solids and Structures, 36: 3443-3468.

  3. [3] Quek, S., Wang, Q. Zhang, L., and Ang, K. 2001. Sensitivity analysis of crack detection in beams by wavelet techniques. International Journal of Mechanical Sciences,. 43: 2899-2910.

  4. [4] Abdo, M. A. B. and Hori, M. 2001. A numerical study of structural damage detection using changes in the rotation of mode shapes. Journal of sound and vibration, 251, 2: 227-239.

  5. [5] Hong, J. C., Kim, Y. Y., Lee, H.C., and Lee, Y, W., 2002. Damage detection us-ing Lipschtiz exponent estimated by the wavelet transform: applications to vibration modes of a beam. International Journal of Solids and Structures. l39, 1803-1816.

  6. [6] Kim, T. J., Ryu, Y. S., Cho, H. M., and Stubbs, N. 2003. Damage identification in beam type structures: frequency based method vs. mode shape based method, Engineering Structures, l, 25: 57-67.

  7. [7] Douka. E., Loutridis. S and Trochidis. A. 2004. Crack identification in plates using wavelet analysis. Journal of sound and vibration. 270: 279-295.

  8. [8] Chang, C. C. and Chen, L. W. 2004. Damage detection of a rectangular plate by spatial wavelet approach, Journal of Applied Acoustics. 65: 819-832.

  9. [9] Chang, C. C. and Chen, L. W. 2005. Detection of the location and size of cracks in the multiple cracked beam by spatial wavelet based approach. International Journal of mechanical systems and signal processing, 19: 139-145.

  10. [10] Rucka. M. and Wilde. K, 2006, Applications of continuous wavelet transform in vibration based damage detection method for beam and plates. Journal of sound and vibration, 15: 143-149.

  11. [11] Grossmann, A. and Morlet. J. 1984. Decomposition of hardy functions into square integrable wavelet of constant shape. SIAM Journal of Mathematical Analysis, 15: 723-736.

  12. [12] Mallat, 1989. A Theory for Multi-resolution Signal Decomposition: The Wavelet Representation. IEEE, Pattern Analysis and Machine Intelligence, 11, 7: 659-674.

  13. [13] Daubechies 1992. Ten Lectures on Wavelets. Presented in CBS-NSF Regional Conference in Applied Mathematics.


ARTICLE INFORMATION


Received: 2011-09-01
Revised: 2011-10-14
Accepted: 2012-01-13
Available Online: 2012-03-01


Cite this article:

Reddy, D.M., Swarnamani, S. 2012. Damage detection and identification in structures by spatial wavelet based approach. International Journal of Applied Science and Engineering, 10, 69–87. https://doi.org/10.6703/IJASE.2012.10(1).69


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