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Inverse structural damage identification problem in CFRP laminated plates using SFO algorithm based on strain fields
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DOI：10.1007/s00366-020-01027-6.png)
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Damage detection methods are an important field of engineering and crucial in terms of structural safety. However, in many practical cases, the process of monitoring and identifying damage is extremely difficult or even impractical due to the conditions of access and operation of a given component/structure. In this study, an inverse algorithm based on strain fields for damage identification in composite plate structures is presented. The inverse analyses combine experimental tests and digital image correlation (DIC) with numerical models based on finite element update method with great advantage of being a non-contact method. The proposed technique identifies the location and dimension of damages in a CFRP plate using static strains formulated as an objective function to be minimized. By model updating, the discrepancies between the experimental and the numerical results are minimized. For the success of the model updating, the efficiency of the optimization algorithm is essential. A powerful new metaheuristic sunflower optimization (SFO) is employed to update the unknown model parameters. Experimental results showed the excellent efficiency in the combined use of DIC, numerical modeling and SFO optimization to accurately identify the location of damage in numerical and experimental tests. The obtained results indicate that the proposed method can be used to determine efficiently the location and dimension of structural damages in mechanical structures.
Keyword:
Structural health monitoring
Inverse problem
Sunflower optimization
Digital image correlation
Composite plates
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