Forming Complicated Surface in Shipyard Using Neural Network System

Abstract

Determining the positions of triangle heating in and parameters of heating process are important for deforming the concave surfaces in shipyard, as well as airplane. The objective of this study was to develop an artificial neural network (ANN) model to predict positions of induction heating and parameters of heating process based on analytical solutions. This model of ANN can help manufacturers determine the positions of induction heating lines and their heating parameters to form a desired shape of plate. The back-propagation neural network systems for determining line-heating positions from object shape of plate are presented in this paper. An artificial neural network model is developed with the relationship between the desired shape of plate and the paths of induction heating. The input data are vertical displacements of plate and the output data are selected heating lines composed by the areas. The outputs of the models were positions of induction heating on plate as well as their parameters. Simulated values obtained with neural network correspond closely to the experimental results.