标题:Digital twin modeling method for CNC machine tool
作者:Luo, Weichao ;Hu, Tianliang ;Zhu, Wendan ;Tao, Fei
通讯作者:Hu, Tianliang
作者机构:[Luo, Weichao ;Hu, Tianliang ;Zhu, Wendan ] School of Mechanical Engineering, Shandong University, Jinan; 250061, China;[Tao, Fei ] School of Automati 更多
会议名称:15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018
会议日期:27 March 2018 through 29 March 2018
来源:ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control
出版年:2018
页码:1-4
DOI:10.1109/ICNSC.2018.8361285
关键词:CNC machine tool (CNCMT); Digital Twin (DT); Fault predict and diagnosis; Smart manufacturing
摘要:CNC machine tool (CNCMT) is the mother machine of industry, which plays an important role in the coming smart manufacturing. The intelligence of CNCMT has a big significance, which will enables its self-sensing, self-prediction and self-maintenance without user concerns. In order to realize the intelligence of CNCMT, a Digital Twin (DT) modeling method for CNCMT is researched, including a multi-domain unified modeling method, a mapping method and an autonomous strategy. This paper provides a demonstration of DT modeling method for CNCMT. © 2018 IEEE.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048211080&doi=10.1109%2fICNSC.2018.8361285&partnerID=40&md5=c881c5611d9cc0c6ceb9029dc7bc2f2f
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