Reliability analysis based on cyber⁃physical system and digital twin

被引：0
|
作者：
Song L. [1 ,2 ]
Wang L.-P. [2 ,3 ]
Wu J. [3 ]
Guan L.-W. [3 ]
Liu Z.-G. [2 ]
机构：
[1] College of Intelligent Manufacturing, Panzhihua University, Panzhihua
[2] College of Information Engineering, Southwest University of Science and Technology, Mianyang
[3] Department of Mechanical Engineering, Tsinghua University, Beijing
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2022年 / 52卷 / 02期
关键词：
CNC equipment; Cyber-physical system; Deep learning; Digital twin; Mechanical manufacturing and automation; Reliability analysis;
D O I：
10.13229/j.cnki.jdxbgxb20211230
中图分类号：
学科分类号：
摘要：
In view of the lack of unified integrated system framework and algorithm implementation for reliability analysis of CNC equipment in practical application, in this paper, a cyber-physical system based on digital twin is proposed, and the specific framework and algorithm implementation are studied. The closed-loop control from the physical layer to the cyber layer and back to the physical layer can be realized through the 7-step workflow of data acquisition, data processing, digital twin model training and evaluation, model debugging and optimization, model online deployment, reliability analysis, predictive maintenance. The feasibility and effectiveness of the cyber-physical system framework were verified by the reliability experiment of spindle rotation error prediction of CNC equipment. This method can analyze the reliability of CNC equipment, and is helpful to support more effective and scientific predictive maintenance. © 2022, Jilin University Press. All right reserved.
引用
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页码：439 / 449
页数：10
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