Artificial Intelligence Applied to Microwave Heating Systems: Prediction of Temperature Profile through Convolutional Neural Networks

Author:

Rosario Núñez Victor1ORCID,Hernández Alfonso1ORCID,Rodríguez Iván1,Fernández-Pacheco Ruiz Ignacio1ORCID,Acevedo Luis1ORCID

Affiliation:

1. Idener Research and Development, 41300 Seville, Spain

Abstract

Microwave heating, which is caused by the interaction of electromagnetic radiation and materials, has become an important component in industrial operations across numerous industries. Despite their importance, conventional numerical simulations of microwave heating are computationally intensive. Concurrently, advances in artificial intelligence (AI), particularly machine learning algorithms, have transformed data processing by increasing accuracy while decreasing computational time. This study tackles the difficulty of efficient and accurate modelling in microwave heating by combining convolutional neural networks (CNNs) with traditional simulation techniques. The major goal of this research is to use CNNs to forecast temperature profiles in a variety of industrial materials, including susceptors, semi-transparent, and microwave-transparent materials, under varying power settings and heating periods. This unique strategy greatly reduces prediction times, with up to 60-fold speed increases over standard methods. Our research is based on examining the electromagnetic and thermal responses of these materials under microwave heating. This study’s findings emphasise the need for extensive datasets and show the transformational potential of CNNs in optimising material processing. It uses artificial intelligence to pave the way for more effective and exact simulations, supporting breakthroughs in industrial microwave heating applications.

Funder

European Union’s Horizon Europe

Publisher

MDPI AG

Reference27 articles.

1. Microwave technology: A novel approach to the transformation of natural metabolites;Hu;Chin. Med.,2021

2. Exergy transfer principles of microwavable materials under electromagnetic effects;Acevedo;Mater. Today Commun.,2021

3. Industrial microwave dryer: An effective design to reduce non-uniform heating;Hazervazifeh;Eng. Agric. Environ. Food,2019

4. Metaxas, A.C., and Roger, J.M. (1983). Industrial Microwave Heating, P. Peregrinus on behalf of the Institution of Electrical Engineers Peter Peregrinus Ltd.

5. Can the container-dielectrics control heating patterns for microwave assisted material processing? A finite element based introspection;Bhattacharya;Int. J. Heat Mass Transf.,2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3