Research on deformation prediction of CFETR multi-purpose overloaded robot based on real-time structural simulator

IF 1.9 3区 工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY
Zhixin Yao , Guodong Qin , Muquan Wu , Congju Zuo , Tao Zhang
{"title":"Research on deformation prediction of CFETR multi-purpose overloaded robot based on real-time structural simulator","authors":"Zhixin Yao ,&nbsp;Guodong Qin ,&nbsp;Muquan Wu ,&nbsp;Congju Zuo ,&nbsp;Tao Zhang","doi":"10.1016/j.fusengdes.2024.114709","DOIUrl":null,"url":null,"abstract":"<div><div>The CFETR Multi-Purpose Overload Robot (CMOR) is a key subsystem of the China Fusion Engineering Test Reactor (CFETR), which can perform maintenance tasks of the internal components. However, the large slenderness ratio of the structure results in low control accuracy of the CMOR end-effector. This paper proposes a CMOR deformation prediction method based on the real-time structural simulator. The overall deformation model of CMOR is analyzed based on the single joint deformation mechanism. Based on the principle of layered control, the control framework of the CMOR structural simulator is constructed, and the deformation data of CMOR in different positions are calculated based on the finite element method. A hybrid neural network containing a multilayer perceptron, transformer, and attention mechanism is designed to train the CMOR deformation prediction model. The training results show that the deformation prediction model converges quickly and fits the deformation of the CMOR structure well with small prediction errors. Finally, the real-time structure simulator is developed based on the deformation prediction model, and the deformation of CMOR is reconstructed with the update frequency of 2 Hz and the absolute error at any point within ±10 mm, which verifies the correctness of the CMOR structural deformation prediction method.</div></div>","PeriodicalId":55133,"journal":{"name":"Fusion Engineering and Design","volume":"209 ","pages":"Article 114709"},"PeriodicalIF":1.9000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fusion Engineering and Design","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S092037962400560X","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NUCLEAR SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

The CFETR Multi-Purpose Overload Robot (CMOR) is a key subsystem of the China Fusion Engineering Test Reactor (CFETR), which can perform maintenance tasks of the internal components. However, the large slenderness ratio of the structure results in low control accuracy of the CMOR end-effector. This paper proposes a CMOR deformation prediction method based on the real-time structural simulator. The overall deformation model of CMOR is analyzed based on the single joint deformation mechanism. Based on the principle of layered control, the control framework of the CMOR structural simulator is constructed, and the deformation data of CMOR in different positions are calculated based on the finite element method. A hybrid neural network containing a multilayer perceptron, transformer, and attention mechanism is designed to train the CMOR deformation prediction model. The training results show that the deformation prediction model converges quickly and fits the deformation of the CMOR structure well with small prediction errors. Finally, the real-time structure simulator is developed based on the deformation prediction model, and the deformation of CMOR is reconstructed with the update frequency of 2 Hz and the absolute error at any point within ±10 mm, which verifies the correctness of the CMOR structural deformation prediction method.
基于实时结构模拟器的 CFETR 多用途超载机器人变形预测研究
中国聚变工程试验堆多用途过载机器人(CMOR)是中国聚变工程试验堆(CFETR)的一个关键子系统,可执行内部组件的维护任务。然而,由于结构的纤度比大,导致 CMOR 末端执行器的控制精度较低。本文提出了一种基于实时结构模拟器的 CMOR 变形预测方法。基于单关节变形机理,分析了 CMOR 的整体变形模型。根据分层控制原理,构建了 CMOR 结构模拟器的控制框架,并基于有限元法计算了 CMOR 不同位置的变形数据。设计了一个包含多层感知器、变压器和注意机制的混合神经网络来训练 CMOR 变形预测模型。训练结果表明,变形预测模型收敛速度快,能很好地拟合 CMOR 结构的变形,预测误差小。最后,基于变形预测模型开发了实时结构模拟器,并重建了 CMOR 的变形,更新频率为 2 Hz,任意点的绝对误差在 ±10 mm 以内,验证了 CMOR 结构变形预测方法的正确性。
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 求助全文
来源期刊
Fusion Engineering and Design
Fusion Engineering and Design 工程技术-核科学技术
CiteScore
3.50
自引率
23.50%
发文量
275
审稿时长
3.8 months
期刊介绍: The journal accepts papers about experiments (both plasma and technology), theory, models, methods, and designs in areas relating to technology, engineering, and applied science aspects of magnetic and inertial fusion energy. Specific areas of interest include: MFE and IFE design studies for experiments and reactors; fusion nuclear technologies and materials, including blankets and shields; analysis of reactor plasmas; plasma heating, fuelling, and vacuum systems; drivers, targets, and special technologies for IFE, controls and diagnostics; fuel cycle analysis and tritium reprocessing and handling; operations and remote maintenance of reactors; safety, decommissioning, and waste management; economic and environmental analysis of components and systems.
×
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