Study on the Integrated Optimization of Heating Furnace Production Process

Tianyi Lu, Qiong Xia, Liangliang Sun, Yupeng Li, Wanying Zhu, Juan Wang, Baolong Yuan, Yi Pan
{"title":"Study on the Integrated Optimization of Heating Furnace Production Process","authors":"Tianyi Lu, Qiong Xia, Liangliang Sun, Yupeng Li, Wanying Zhu, Juan Wang, Baolong Yuan, Yi Pan","doi":"10.1109/IAI53119.2021.9619305","DOIUrl":null,"url":null,"abstract":"The objective of this paper is to optimise the slab heating process in a dynamic environment. Considering the nonlinear and hysteresis characteristics of slab heating in the furnace production process, an operational optimisation model based on a mixture of mechanism and data and a predictive control model for the furnace are developed. The operation optimisation model determines the current optimal furnace temperature distribution based on the desired slab temperature and the current slab temperature, which is then fed into the predictive control model. The predictive control model uses a rolling optimisation method to predict the furnace temperature and adjusts the fuel flow to change the furnace temperature with the desired temperature as the target, thus enabling the slab to reach the desired temperature through an integrated optimisation method. Finally, a large number of simulation data experiments prove that the furnace temperature change process meets the set requirements, and the goal of improving the production process of the heating furnace is achieved.","PeriodicalId":106675,"journal":{"name":"2021 3rd International Conference on Industrial Artificial Intelligence (IAI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Conference on Industrial Artificial Intelligence (IAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAI53119.2021.9619305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The objective of this paper is to optimise the slab heating process in a dynamic environment. Considering the nonlinear and hysteresis characteristics of slab heating in the furnace production process, an operational optimisation model based on a mixture of mechanism and data and a predictive control model for the furnace are developed. The operation optimisation model determines the current optimal furnace temperature distribution based on the desired slab temperature and the current slab temperature, which is then fed into the predictive control model. The predictive control model uses a rolling optimisation method to predict the furnace temperature and adjusts the fuel flow to change the furnace temperature with the desired temperature as the target, thus enabling the slab to reach the desired temperature through an integrated optimisation method. Finally, a large number of simulation data experiments prove that the furnace temperature change process meets the set requirements, and the goal of improving the production process of the heating furnace is achieved.
加热炉生产过程集成优化研究
本文的目的是在动态环境下优化板坯加热过程。针对加热炉生产过程中板坯加热的非线性和滞后特性,建立了基于机理和数据相结合的加热炉运行优化模型和预测控制模型。运行优化模型根据期望坯温和当前坯温确定当前最优炉温分布,并将其输入预测控制模型。预测控制模型采用滚动优化方法预测炉温,并以期望温度为目标,调节燃料流量改变炉温,从而通过综合优化方法使坯体达到期望温度。最后,通过大量仿真数据实验证明,加热炉变温过程满足设定要求,达到了改进加热炉生产工艺的目的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信