학술논문

A Numerical Twin Model for the Coupled Field Analysis of TEAM Workshop Problem 36
Document Type
Periodical
Source
IEEE Transactions on Magnetics IEEE Trans. Magn. Magnetics, IEEE Transactions on. 59(5):1-4 May, 2023
Subject
Fields, Waves and Electromagnetics
Billets
Convolutional neural networks
Computational modeling
Temperature distribution
Inductors
Heating systems
Databases
Convolutional neural network (CNN)
coupled problems
testing electromagnetic analysis method (TEAM) problem
Language
ISSN
0018-9464
1941-0069
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.