安格拉1号核电站管壁厚度测量的数字孪生模型与工业4.0技术

Rogério Adas Pereira Vitalli, João Manoel Losada Moreira
{"title":"安格拉1号核电站管壁厚度测量的数字孪生模型与工业4.0技术","authors":"Rogério Adas Pereira Vitalli, João Manoel Losada Moreira","doi":"10.51219/jaimld/rogerio-adas-pereira-vitalli/08","DOIUrl":null,"url":null,"abstract":"organization. The robotic system is developed using “Digital Twin” technology, a very realistic virtual modeling scheme that allows interaction with the real world environment. They include equipment and all the steps to carry out the inspection process. The tube wall thickness monitoring system will be used at the Angra 1 nuclear power plant (Brazil).","PeriodicalId":487259,"journal":{"name":"Journal of Artificial Intelligence Machine Learning and Data Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mathematical Modeling of Digital Twins and Industry 4.0 Technologies for Measuring Pipe Wall Thickness at Angra 1 Nuclear Power Plant\",\"authors\":\"Rogério Adas Pereira Vitalli, João Manoel Losada Moreira\",\"doi\":\"10.51219/jaimld/rogerio-adas-pereira-vitalli/08\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"organization. The robotic system is developed using “Digital Twin” technology, a very realistic virtual modeling scheme that allows interaction with the real world environment. They include equipment and all the steps to carry out the inspection process. The tube wall thickness monitoring system will be used at the Angra 1 nuclear power plant (Brazil).\",\"PeriodicalId\":487259,\"journal\":{\"name\":\"Journal of Artificial Intelligence Machine Learning and Data Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Artificial Intelligence Machine Learning and Data Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.51219/jaimld/rogerio-adas-pereira-vitalli/08\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Artificial Intelligence Machine Learning and Data Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.51219/jaimld/rogerio-adas-pereira-vitalli/08","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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
Mathematical Modeling of Digital Twins and Industry 4.0 Technologies for Measuring Pipe Wall Thickness at Angra 1 Nuclear Power Plant
organization. The robotic system is developed using “Digital Twin” technology, a very realistic virtual modeling scheme that allows interaction with the real world environment. They include equipment and all the steps to carry out the inspection process. The tube wall thickness monitoring system will be used at the Angra 1 nuclear power plant (Brazil).
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Synthesizing Sentience: Integrating Large Language Models and Autonomous Agents for Emulating Human Cognitive Complexity Effective Strategies for Mitigating Bias in Hiring Algorithms: A Comparative Analysis Ethical Use of Artificial Intelligence and New Technologies in Education 5.0 Human-Robot Interaction: A state of the art review Wheel-Rail Force Identification Method Based on CNN-BiLSTM Hybrid Model
×
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