A numerical twin model for the magneto-thermal analysis of an induction heating device is proposed. The non-linearity of magnetic permeability against temperature - which characterizes the workpiece - is captured by the model, while the use of a convolutional neural network (CNN), trained by a number of finite-element (FE) analyses, makes it possible to solve the following inverse problem: given a temperature map in the workpiece section, identify current and relevant frequency in the inductor coil, as well as the time instant at which the map refers to. The testing electromagnetic analysis method (TEAM) problem 36 is considered as the case study.
A Numerical Twin Model for the Coupled Field Analysis of TEAM Workshop Problem 36
Di Barba P.;Mognaschi M. E.
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2023-01-01
Abstract
A numerical twin model for the magneto-thermal analysis of an induction heating device is proposed. The non-linearity of magnetic permeability against temperature - which characterizes the workpiece - is captured by the model, while the use of a convolutional neural network (CNN), trained by a number of finite-element (FE) analyses, makes it possible to solve the following inverse problem: given a temperature map in the workpiece section, identify current and relevant frequency in the inductor coil, as well as the time instant at which the map refers to. The testing electromagnetic analysis method (TEAM) problem 36 is considered as the case study.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
