Quantification of Damages in Laminated Composite Plates through Artificial Neural Network utilizing Generalized Flexibility Method

Abstract

In this paper, single and many damages are detected at different places of the three-layered laminated cross-ply (0°/90°/0°) composite plate using Generalized Flexibility Energy Quotient Difference Method (GFEQDM) utilizing the first mode. Only first natural frequency and its mode shape are utilized which constitute the major advantage in the proposed method, as they are easy to capture practically. During the first phase, the Generalized Flexibility Energy Quotient Difference Ratio (β) is calculated at different points on the plate using the elements' reduced modulus of elasticity. In the second phase, the β computed at all locations of the plate for various damaged elements are used as input, in ANN and the damage indices at the damaged locations are taken as output. These results clearly demonstrate the acceptability of the suggested approach, which finds use in averting structural failure. Finally, the damage is quantified by developing the relevant equations.