An integral monitoring concept for data-driven detection and localization of incipient leakages by fusion of process and environment data

Kristian Kasten, Caroline Charlotte Zhu, Joachim Birk, Steven X. Ding
{"title":"An integral monitoring concept for data-driven detection and localization of incipient leakages by fusion of process and environment data","authors":"Kristian Kasten,&nbsp;Caroline Charlotte Zhu,&nbsp;Joachim Birk,&nbsp;Steven X. Ding","doi":"10.1002/amp2.10133","DOIUrl":null,"url":null,"abstract":"<p>The risk of leakages in process industry is environmentally critical and potentially hazardous. Many technologies and schemes for process monitoring are theoretically developed and applied in an industrial context. Nevertheless, most approaches still focus on individual monitoring of a process and its environment. The major challenge is the lack of <i>a priori</i> knowledge about the leakage. This paper introduces a new approach combining monitoring of the environment and its embedded process. The application on an industrial use-case in a real plant environment illustrates the success of this combined monitoring approach as well as a decision support to localize an incipient leakage.</p>","PeriodicalId":87290,"journal":{"name":"Journal of advanced manufacturing and processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aiche.onlinelibrary.wiley.com/doi/epdf/10.1002/amp2.10133","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of advanced manufacturing and processing","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/amp2.10133","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 risk of leakages in process industry is environmentally critical and potentially hazardous. Many technologies and schemes for process monitoring are theoretically developed and applied in an industrial context. Nevertheless, most approaches still focus on individual monitoring of a process and its environment. The major challenge is the lack of a priori knowledge about the leakage. This paper introduces a new approach combining monitoring of the environment and its embedded process. The application on an industrial use-case in a real plant environment illustrates the success of this combined monitoring approach as well as a decision support to localize an incipient leakage.

Abstract Image

通过过程和环境数据的融合实现数据驱动的早期泄漏检测和定位的整体监测概念
过程工业中的泄漏风险对环境至关重要,具有潜在的危害。许多过程监控的技术和方案都是从理论上发展起来的,并在工业环境中得到了应用。然而,大多数方法仍然侧重于对过程及其环境的单独监视。主要的挑战是缺乏关于泄漏的先验知识。本文介绍了一种将环境监测与嵌入式过程相结合的新方法。在一个真实工厂环境中的工业用例上的应用说明了这种组合监测方法的成功,以及对早期泄漏进行定位的决策支持。
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
CiteScore
4.50
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