Determination of Material Properties of Functionally Graded Plate Using the Dispersion of Guided Waves and an Artificial Neural Network

Abstract

Abstract Using guided wave dispersion characteristics, an inverse method based on artificial neural network (ANN) is presented to determine the material properties of functionally graded materials (FGM) plates. The group velocities of several lowest modes at several lower frequencies are used as the inputs of the ANN model; the outputs of the ANN are the distribution function of the volume fraction of the FGM plate. The Legendre polynomials method is used to calculate the dispersion curves for the FGM plate. Levenberg-Marquardt algorithm is used as numerical optimization to speed up the training process of the ANN model.