Development of an Intelligent Monitoring System Based on the Use of Fiber-Optic Sensors and Deep Learning

A. Neftissov, Assiya Sarinova, Ilyas Kazambaev, L. Kirichenko, S. Bronin
{"title":"Development of an Intelligent Monitoring System Based on the Use of Fiber-Optic Sensors and Deep Learning","authors":"A. Neftissov, Assiya Sarinova, Ilyas Kazambaev, L. Kirichenko, S. Bronin","doi":"10.1109/SIST58284.2023.10223520","DOIUrl":null,"url":null,"abstract":"Fiber-optic sensors are commonly used in modern monitoring systems. This article discusses a monitoring system using a fiber-optic sensor built using a camera. As the study showed, the newly proposed method requires a machine learning system to determine the displacement of stone slabs accurately. However, this system needs to have higher accuracy in determining the distance to the damage. This work aims to develop a deep learning system that considers external disturbances affecting a light spot's image.","PeriodicalId":367406,"journal":{"name":"2023 IEEE International Conference on Smart Information Systems and Technologies (SIST)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Smart Information Systems and Technologies (SIST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIST58284.2023.10223520","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

Fiber-optic sensors are commonly used in modern monitoring systems. This article discusses a monitoring system using a fiber-optic sensor built using a camera. As the study showed, the newly proposed method requires a machine learning system to determine the displacement of stone slabs accurately. However, this system needs to have higher accuracy in determining the distance to the damage. This work aims to develop a deep learning system that considers external disturbances affecting a light spot's image.
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
基于光纤传感器和深度学习的智能监测系统的开发
光纤传感器在现代监控系统中得到广泛应用。本文讨论了一种利用摄像机构建的光纤传感器的监控系统。正如研究表明的那样,新提出的方法需要一个机器学习系统来准确地确定石板的位移。然而,该系统在确定损伤距离方面需要更高的精度。这项工作旨在开发一种深度学习系统,该系统可以考虑影响光点图像的外部干扰。
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
University Distributed Computer Network Vulnerability Assessment Performance Analysis of Scaling NoSQL vs SQL: A Comparative Study of MongoDB, Cassandra, and PostgreSQL Analysis of the EMF Parameters of the Stator Winding in the Run-Down Mode for Diagnosing Faults in an Induction Motor About the Need to Attract Girls to Education Using the Stem Methodology in the Informatics Educational Program Preservation of Confidentiality Based on Homomorphic Encryption Library for IoT
×
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