With the increasing size and complexity of machines and vessels, the inverse problems of continuous bodies are becoming necessary. In this paper the possibility of using a multilayer perceptron network trained with the backpropagation algorithm for identifying the axial force and support condition (or shape parameters) of orthotropic plates is studied. The considered plate model is a tapered rectangular plate, using a transfer matrix method, to estimate the changes in various modal parameters, caused by an axial force, shape parameters and support condition of plates. The basic idea is to train a neural network with simulated patterns of the relative changes in natural frequencies (eigenvalues) and corresponding support condition (or shape parameters) and axial force of plates in order to recognize the behavior of plate. Subjecting this neural network to un-learning values should imply information about the shape parameters and axial force. The training data are obtained by the transfer matrix method.

purchase the full-text of this paper (price £20)

go to the previous paper
go to the next paper
return to the table of contents
return to the book description
purchase this book (price £52 +P&P)