An update method for digital twin multi-dimension models

被引:19
|
作者
Zhang, He [1 ,2 ]
Qi, Qinglin [1 ,3 ]
Ji, Wei [4 ]
Tao, Fei [1 ,5 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[2] Beihang Univ, ShenYuan Hornors Coll, Beijing 100191, Peoples R China
[3] Beihang Univ, Sch Mech Engn & Automat, Beijing 100191, Peoples R China
[4] Sandvik Coromant, S-12679 Stockholm, Sweden
[5] Beihang Univ, Int Res Inst Multidisciplinary Sci, Digital Twin Int Res Ctr, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
Digital twin; Consistency; Model update; Machine tool; Tool wear; FAULT-DIAGNOSIS; FLANK WEAR; TOOL;
D O I
10.1016/j.rcim.2022.102481
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Digital twin, as an effective means to realize the fusion between physical and virtual spaces, has attracted more and more attention in the past few years. Based on ultra-fidelity models, more accurate service, e.g. real-time monitoring and failure prediction, can be reached. Against the background, some scholars studied the related theories and methods on modeling to depict various features of physical objects. Some scholars studied how to use Internet of Things to realize the connections and interactions, thereby keeping the consistency between the virtual and physical spaces. During this process, a new question arises that how to update the models once digital twin models are inconsistent with the practical situations. To solve the problem, this paper proposed a general digital twin model update framework at first. Then, the update methods for multi-dimension models are further explored. The cutting tool is the core component of machine tools which are the key equipment in industry. The precise cutting tool models are essential for realizing the digitalization and servitization of machine tools. Therefore, this paper takes a cutting tool as the application object to discuss how to conduct physics model update based on the proposed framework and methods. Through model update, a more accurate and updated tool wear model could be obtained, which contributes to the prognostics and health management for machine tools.
引用
收藏
页数:10
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