基于神经网络的船厂感应加热路径预测

Truong-Thinh Nguyen, Y. Yang
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引用次数: 0

摘要

本文提出了一种用于感应加热过程中加热线位置预测的人工神经网络模型。该模型可帮助船厂制造商确定感应加热线的位置及其加热参数,以形成所需的板形。以板的垂直位移为输入参数,选用感应加热线为输出参数建立模型。利用解析解预测感应加热过程中钢板变形,得到了神经网络的训练模式。对所建立的神经网络模型进行了验证,证明了该模型在确定平面钢板在线加热过程中加热位置以形成所需形状的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Neural Network for Predicting Induction-heating Paths in Shipyard
This paper presents the development of an artificial neural network model for the prediction of heating-line positions in induction heating process. This model helps shipyard manufacturers determine the positions of induction heating lines and their heating parameters to form a desired shape of plate. The vertical displacements of plate have been considered as the input parameters and the selected induction heating lines as output parameters to develop the model. The training patterns of neural network are obtained using an analytical solution that predicts plate deformations in induction heating process. The developed neural network model is tested to show its feasibility to determine the heating positions on the surface of a flat steel plate in the line heating process for forming a desired shape.
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