Shearography-Wavelet-Based Damage Detection Methodology for Aluminum Beams

Document Type : Regular Paper

Authors

1 M.Sc. Student, Civil Engineering Department, University of Birjand, Birjand, Iran

2 Associate Professor, Department of Civil Engineering, University of Birjand, Birjand, Iran

3 Assistant Professor, Department of Civil Engineering, University of Birjand, Birjand, Iran

4 Professor of Mechanical Engineering, University of Lisbon, Instituto Superior Tecnico, Lisbon, Portugal

5 Assistant Professor, Department of Mechanical Engineering, DEM-ISEP, Instituto Politécnico do Porto, Porto, Portugal

Abstract

In this paper, aluminum beams in undamaged status and with single and double damage scenarios as slots with the ratio of the slot depth to the beam thickness of 7% and 28% were constructed at the University of Lisbon, Portugal. Then, with the help of the shrearography method, the modal rotations of each beam were calculated for the first to third vibration mode shapes. By deriving the modal rotations, the modal strains were obtained and introduced as the input of 22 different families of 2D wavelet transforms with three different scales 1, 7, and 15. Utilizing the wavelet coefficients as damage indices, the results showed that the sensitivity of modal curvatures is higher than other modal data for identifying the location of damages. In addition, among scales 1, 7, and 15, considering scale 7 for wavelet families provides more suitable results. On the other hand, the sinc and isodog wavelet families showed a better ability to reveal the damage location than other wavelets. Investigating the ratio of the maximum value of the wavelet coefficients in the middle part of the beams to the maximum value of the wavelet coefficients in the boundaries showed that among the two selected wavelets, sinc and isodog, the sinc wavelet is more sensitive than the isodog wavelet in identifying damages with obtained results of 0.81, 7.81 and 27.10 for first, second and third damage scenarios, respectively. And therefore, it can be considered the best wavelet for detecting artificial damage in the tested aluminum beams.

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