Intelligent monitoring of the condition of hydrocarbon pipeline transport facilities using neural network technologies

IF 2.4 Q2 MINING & MINERAL PROCESSING
M. Zemenkova, E. Chizhevskaya, Y. Zemenkov
{"title":"Intelligent monitoring of the condition of hydrocarbon pipeline transport facilities using neural network technologies","authors":"M. Zemenkova, E. Chizhevskaya, Y. Zemenkov","doi":"10.31897/pmi.2022.105","DOIUrl":null,"url":null,"abstract":"The national strategic goal of the Russian Federation is to ensure the safety of critical technologies and sectors, which are important for the development of the country's oil and gas industry. The article deals with development of national technology for intelligent monitoring of the condition of industrial facilities for transport and storage of oil and gas. The concept of modern monitoring and safety control system is developed focusing on a comprehensive engineering control using integrated automated control systems to ensure the intelligent methodological support for import-substituting technologies. A set of approved algorithms for monitoring and control of the processes and condition of engineering systems is proposed using modular control robotic complexes. Original intelligent models were developed for safety monitoring and classification of technogenic events and conditions. As an example, algorithms for monitoring the intelligent safety criterion for the facilities and processes of pipeline transport of hydrocarbons are presented. The research considers the requirements of federal laws and the needs of the industry.","PeriodicalId":16398,"journal":{"name":"Journal of Mining Institute","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mining Institute","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31897/pmi.2022.105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MINING & MINERAL PROCESSING","Score":null,"Total":0}
引用次数: 11

Abstract

The national strategic goal of the Russian Federation is to ensure the safety of critical technologies and sectors, which are important for the development of the country's oil and gas industry. The article deals with development of national technology for intelligent monitoring of the condition of industrial facilities for transport and storage of oil and gas. The concept of modern monitoring and safety control system is developed focusing on a comprehensive engineering control using integrated automated control systems to ensure the intelligent methodological support for import-substituting technologies. A set of approved algorithms for monitoring and control of the processes and condition of engineering systems is proposed using modular control robotic complexes. Original intelligent models were developed for safety monitoring and classification of technogenic events and conditions. As an example, algorithms for monitoring the intelligent safety criterion for the facilities and processes of pipeline transport of hydrocarbons are presented. The research considers the requirements of federal laws and the needs of the industry.
应用神经网络技术对油气管道输送设施状态进行智能监测
俄罗斯联邦的国家战略目标是确保关键技术和部门的安全,这对该国石油和天然气工业的发展至关重要。本文论述了我国油气运输和储存工业设施状态智能监测技术的发展情况。现代监控和安全控制系统的概念侧重于使用集成自动化控制系统的综合工程控制,以确保为进口替代技术提供智能方法支持。采用模块化控制机器人复合体,提出了一套用于监控和控制工程系统过程和状态的认可算法。开发了用于安全监测和技术事件和条件分类的原始智能模型。以油气管道输送设施和过程的智能安全标准为例,给出了监控算法。该研究考虑了联邦法律的要求和行业的需求。
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
Journal of Mining Institute
Journal of Mining Institute MINING & MINERAL PROCESSING-
CiteScore
7.50
自引率
25.00%
发文量
62
审稿时长
8 weeks
文献相关原料
公司名称 产品信息 采购帮参考价格
×
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