A Novel Method for Online Detection of FeO Content in Sinter

C. Shao, Zicheng Li, Chenxing Guo
{"title":"A Novel Method for Online Detection of FeO Content in Sinter","authors":"C. Shao, Zicheng Li, Chenxing Guo","doi":"10.1109/AICIT55386.2022.9930289","DOIUrl":null,"url":null,"abstract":"The FeO content of the sinter is one of the essential parameters of the blast furnace smelting process. However, traditional detection methods cannot achieve accurate online measurement. In this paper, based on analyzing the composition and ferromagnetism of various substances in sinter, a novel magnetic method for online measurement of sinter FeO content is proposed. It uses the magnetic attraction of NdFeB permanent magnets on the ferromagnetic substances to find out the sinter FeO content. The 3D modeling of NdFeB permanent magnets and sinter in the Maxwell electromagnetic module of ANSYS software was performed, and the magnetic finite element analysis of sinter in different states was carried out. Simulation results show that the magnetic attraction force between the permanent magnet and the sinter obviously changes with the variation of the sinter FeO content. The proposed scheme for the online measurement of sinter FeO content in sinter is also validated by simulation results.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICIT55386.2022.9930289","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 FeO content of the sinter is one of the essential parameters of the blast furnace smelting process. However, traditional detection methods cannot achieve accurate online measurement. In this paper, based on analyzing the composition and ferromagnetism of various substances in sinter, a novel magnetic method for online measurement of sinter FeO content is proposed. It uses the magnetic attraction of NdFeB permanent magnets on the ferromagnetic substances to find out the sinter FeO content. The 3D modeling of NdFeB permanent magnets and sinter in the Maxwell electromagnetic module of ANSYS software was performed, and the magnetic finite element analysis of sinter in different states was carried out. Simulation results show that the magnetic attraction force between the permanent magnet and the sinter obviously changes with the variation of the sinter FeO content. The proposed scheme for the online measurement of sinter FeO content in sinter is also validated by simulation results.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
烧结矿中FeO含量在线检测的新方法
烧结矿的FeO含量是高炉冶炼过程的重要参数之一。然而,传统的检测方法无法实现准确的在线测量。本文在分析烧结矿中各种物质的组成和铁磁性的基础上,提出了一种在线测量烧结矿FeO含量的新型磁法。它利用钕铁硼永磁体对铁磁性物质的磁力来测定烧结矿中FeO的含量。在ANSYS软件的Maxwell电磁模块中对NdFeB永磁体和烧结矿进行了三维建模,并对烧结矿在不同状态下进行了磁性有限元分析。仿真结果表明,永磁体与烧结矿之间的磁性引力随烧结矿FeO含量的变化而发生明显变化。仿真结果验证了所提出的烧结矿FeO含量在线测量方案的有效性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Maritime Object Detection based on YOLOx for Aviation Image STATCOM compensation and control strategy of star cascade H-bridge under unbalanced conditions Detection and Recognition of Road Information and Lanes Based on Deep Learning Event Extraction for Military Target Motion in Open-source Military News A Similarity Measurement Algorithm for Spacecraft Telemetry Time Series
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1