标题:Digital twin for CNC machine tool: modeling and using strategy
作者:Luo, Weichao; Hu, Tianliang; Zhang, Chengrui; Wei, Yongli
作者机构:[Luo, Weichao; Hu, Tianliang; Zhang, Chengrui; Wei, Yongli] Shandong Univ, Sch Mech Engn, Jinan 250061, Shandong, Peoples R China.; [Luo, Weichao; H 更多
通讯作者:Hu, Tianliang;Hu, TL;Hu, TL;Hu, TL
通讯作者地址:[Hu, TL]Shandong Univ, Sch Mech Engn, Jinan 250061, Shandong, Peoples R China;[Hu, TL]Shandong Univ, Minist Educ, Key Lab High Efficiency & Clean Mech 更多
来源:JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
出版年:2019
卷:10
期:3
页码:1129-1140
DOI:10.1007/s12652-018-0946-5
关键词:CNC machine tool (CNCMT); Digital twin (DT); Smart manufacturing
摘要:As a typical manufacturing equipment, CNC machine tool (CNCMT), which is the mother machine of industry, plays an important role in the new trend of smart manufacturing. As the requirement of smart manufacturing, the abilities of its self-sensing, self-prediction and self-maintenance are necessary. In order to make CNCMT become more intelligent, a research about Digital twin (DT) for CNCMT is conducted. In this research, a multi-domain unified modeling method of DT is established, a mapping strategy between physical space and digital space is explored, and an autonomous strategy of DT is proposed. These methods can optimize the running mode, reduce the sudden failure probability and improve the stability of CNCMT. Finally, this paper provides a demonstration of DT model building and using strategy in fault prediction and diagnosis for CNC milling machine tool.
收录类别:EI;SCOPUS;SCIE
WOS核心被引频次:1
Scopus被引频次:4
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050765931&doi=10.1007%2fs12652-018-0946-5&partnerID=40&md5=86251785fba73c48540b39916a86873e
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