Multi-scale evolution mechanism and knowledge construction of a digital twin mimic model

Liu, Shimin; Lu, Yuqian; Li, Jie; Song, Dengqiang; Sun, Xiao‐Feng; Bao, Jinsong

doi:10.1016/j.rcim.2021.102123

Cited by 56 publications

(8 citation statements)

References 34 publications

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“…Subsequently, a DT-enhanced Industrial Internet (DT-II) reference framework for smart manufacturing was proposed. Liu, et al [33] investigated the multi-scale evolution mechanism of the DT model and constructed a DT quality knowledge model at macro, meso, and micro levels. DT technology is used extensively in the manufacturing industry.…”

Section: Digital Twin-driven Machining Processmentioning

confidence: 99%

Digital Twin-Driven Tool Wear Monitoring and Predicting Method for the Turning Process

et al. 2021

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Accurate monitoring and prediction of tool wear conditions have an important influence on the cutting performance, thereby improving the machining precision of the workpiece and reducing the production cost. However, traditional methods cannot easily achieve exact supervision in real time because of the complexity and time-varying nature of the cutting process. A method based on Digital Twin (DT), which establish a symmetrical virtual tool system matching exactly the actual tool system, is presented herein to realize high precision in monitoring and predicting tool wear. Firstly, the framework of the cutting tool system DT is designed, and the components and operations rationale of the framework are detailed. Secondly, the key enabling technologies of the framework are elaborated. In terms of the cutting mechanism, a virtual cutting tool model is built to simulate the cutting process. The modifications and data fusion of the model are carried out to keep the symmetry between physical and virtual systems. Tool wear classification and prediction are presented based on the hybrid-driven method. With the technologies, the physical–virtual symmetry of the DT model is achieved to mapping the real-time status of tool wear accurately. Finally, a case study of the turning process is presented to verify the feasibility of the framework.

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Section: Digital Twin-driven Machining Processmentioning

confidence: 99%

Digital Twin-Driven Tool Wear Monitoring and Predicting Method for the Turning Process

et al. 2021

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“…In this paper, the system service is concretized as predicting the leakage characteristics of spool valve, that is, analyzing the mating performance of the spool valve using the physical spool valve, digital twin spool valve and relevant data. The digital twin data refers to all the data associated with the digital twin, which are used to realize the fusion of virtual space and real space, the interaction of virtual space and real space and the prediction and analysis of real behavior of real objects in the real word [18,22]. In this paper, it refers to the actually measured data and calculation data gained from the physical spool valve and the digital twin spool valve to support the virtual-real interaction process.…”

Section: Overall Framework Of Analyzing Mating Performance Of Precision Spool Valves Based On Digital Twinmentioning

confidence: 99%

“…The multi-disciplinary, multi-scale, multi-probability and high-fidelity digital twin technology facilitates the interaction and integration of physical space and virtual space, which avoids inaccurate analysis and prediction caused by the inconsistency between virtual and real states [18][19][20]. Currently, studies have been carried out on the application of the digital twin technology in product design [21], process planning [22,23], dynamic scheduling [24,25] and quality monitoring [26,27]. Instructive research results have been obtained, but the digital twin technology is still rapidly developing.…”

Section: Introductionmentioning

confidence: 99%

Digital Twin-Driven Mating Performance Analysis for Precision Spool Valve

Tang

Zhang

et al. 2021

Machines

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The precision spool valve is the core component of the electro-hydraulic servo control system, and its performance has an important influence on the flight control of aviation and aerospace products. The non-uniform surface topography error causes a non-uniform mating gap field inside the spool valve, which causes oil leakage and leads to deterioration of the spool valve performance. However, the current oil leakage calculation method only considers the influence of size errors, which is not comprehensive. Thus, how to characterize the mating behavior of the spool valve and its effect on oil leakage with consideration of surface topography errors is the key to evaluating the performance of the spool valve. This paper proposes a new way of analyzing the mating performance of precision spool valves, which considers the surface topography errors based on digital twin technology. Firstly, a general framework for the analysis of mating performance of precision spool valve based on a digital twin is proposed. Then, key technologies of assembly interface geometry modeling, matching behavior modeling and performance analysis are studied. Finally, a quantitative correlation between the mating parameters and the oil leakage of the precision spool valve is revealed. The method is tested on a practical case. This proposed method can provide theoretical support for the accurate prediction and evaluation of the mating performance of the precision spool valve.

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“…Researchers [14] make use of semantic models to describe the rules, computing processes and interrelationships related to computing models in order to support automatic decision-makings. Targeting at the manufacturing domain applications, a decision-making DT platform based semantic models is proposed for monitoring and controlling the machining quality [15].…”

Section: Introductionmentioning

confidence: 99%

Exploring the concept of Cognitive Digital Twin from model-based systems engineering perspective

Zhaorui

Zheng

et al. 2022

Int J Adv Manuf Technol

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Digital Twin technology has been widely applied in various industry domains. Modern industrial systems are highly complex consisting of multiple interrelated systems, subsystems and components. During the lifecycle of an industrial system, multiple digital twin models might be created related to different domains and lifecycle phases. The integration of these relevant models is crucial for creating higher-level intelligent systems. The Cognitive Digital Twin (CDT) concept has been proposed to address this challenge by empowering digital twins with augmented semantic capabilities. It aims at identifying the dynamics and interrelationships of virtual models, thus to enhance complexity management capability and to support decision-making during the entire system lifecycle. This paper aims to explore the CDT concept and its core elements following a systems engineering approach. A conceptual architecture is designed according to the ISO 42010 standard to support CDT development; and an application framework enabled by knowledge graph is provided to guide the CDT applications. In addition, an enabling tool-chain is proposed corresponding to the framework to facilitate the implementation of CDT. Finally, a case study is conducted, based on simulation experiments as a proof-of-concept.

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Multi-scale evolution mechanism and knowledge construction of a digital twin mimic model

Cited by 56 publications

References 34 publications

Digital Twin-Driven Tool Wear Monitoring and Predicting Method for the Turning Process

Digital Twin-Driven Tool Wear Monitoring and Predicting Method for the Turning Process

Digital Twin-Driven Mating Performance Analysis for Precision Spool Valve

Exploring the concept of Cognitive Digital Twin from model-based systems engineering perspective

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