<title>Estimation of contact force on composite plates using impact-induced strain and neural network</title>

Abstract

A method of determining the contact force on laminated composite plates subjected to low velocity impact is developed using the finite element method and a neural network. The back propagation neural network is used to estimate the contact force on the composite plates using the strain signals. The neural network is trained using the contact force and strain histories obtained from finite element simulation results. The finite element model is based on a higher order shear deformation theory and accounts for von-Karman nonlinear strain-displacement relations. The nonlinear time dependent equations are solved using a direct iteration scheme in conjunction with the Newmark time integration scheme. The training process consists of training the network with strain signals at three different locations. The effectiveness of different neural network configurations for estimating contact force is investigated. The neural network approach to the estimation of contact force proved to be a promising alternative to more traditional techniques, particularly for an on-line health monitoring system.