DEFECTS IDENTIFICATION IN MICROPOLAR MATERIALS
This paper uses the micropolar nonlinear wave theory in order to develop an inverse approach for capturing the size and location of inhomogeneities embedded into a micropolar material. We specify that the inhomogeneities have dimensions comparable to the average grain size of the material. The natural frequencies of a structure represent its signature of the dynamic behaviour, and any defect or change into the internal structure of the material is felt by the vibrations in the sense of modifying their natural frequencies. Based on the analysis of the interrelations between natural frequencies and the structure of the material, an unconstrained minimization algorithm is built by minimization of the least square distance between computed and measured natural frequencies. We show that the effect of the size and location of the defects on the natural frequencies of the structures is a real feature that helps us to identify defects into the material.
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