Wavelet transform-based damage identification in laminated composite beams based on modal and strain data

Abstract

Laminated composite structures suffer from delamination, the detachment of the layers due to the rupture of the fiber-matrix interface, as their principal mode of failure. In contrast to other damages, such as cracks, delaminations are often not visible on the surface, causing late detection and leading to sudden failures. To ensure that laminated composite structures operate flawlessly, precise monitoring methods are required. This work proposes a damage index composed of coefficients obtained from applying a Discrete Wavelet Transform to the mode shapes of a laminated composite beam with the purpose of identifying delaminations. Numerical damages were induced by reducing the stiffness in specific locations in order to simulate different damage cases and then providing data for the coefficient optimization in the damage index. After promising results for identifying damage in numerical cases, the damage index’s efficiency was tested with real carbon fiber-reinforced polymer beams. The experimental specimens were manufactured with delaminations induced by embedding non-sticking films between the layers. Again, high quality results in identifying damage were achieved. The damage index proved efficient at locating damage in almost all positions along the beam, just having issues at the free end due to the discontinuity of the signal. The same specimens were subjected to tensile stress below the yield point to obtain the strain fields of the structure through the Digital Image Correlation technique. A Discrete Wavelet Transform was applied to the strain fields, aiming to identify the delaminations. It is important to emphasize that the proposed damage index is a no-baseline method, a method that does not require information about the pristine structure.

Keywords:

• Damage identification
• wavelet transform
• structural health monitoring
• composites
• modal testing

Acknowledgments

The authors are grateful to the Brazilian Funding Institution FAPEMIG (Grant number APQ-00385-18) for the financial supports.

Data availability statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Disclosure statement

The authors declare that they have no conflict of interest.

Additional information

Funding

This work was supported by Conselho Nacional de Desenvolvimento Cientıfico e Tecnologico; Fundação de Amparo a Pesquisa do Estado de Minas Gerais; Fundação de Amparo a Pesquisa do Estado de São Paulo.