I ISSN: 2414 301 nternational Core Journal of Engineering-1895 Volume 6 Issue 5, 2020 DOI: 10.6919/ICJE.20200 5_6( ).0043 Digital Model of Substation Inspection System Based on Digital Twin Youchan Zhu 1, a, Sai Gao1, b 1School of control and Computer Engineering, North China Electric Power University
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· Machine learning (ML) models, especially large pretrained deep learning (DL) models, are of high economic value and must be properly protected with regard to intellectual property rights (IPR). Model watermarking methods are proposed to embed watermarks into the target model, so that, in the event it is stolen, the model’s owner
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This study creates a different approach by adding structural topology to build a new category of recommendation platform using the digital twin model with real-time data collected by
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· Insets show 3D digital models representing compound lattices inversely designed by the ML-predicted design gradients (G 1: unit cell gradient, G 2: strut radius ratio gradient, G 3: inclined strut
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A Digital Twin (DT) is a set of computer-generated models that map a physical object into a virtual space. Both physical and virtual elements exchange information to monitor,
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· The Digital Human Model (DHM) is a computational technique employed for simulating human motion and behavior, finding applications across sectors such as manufacturing, healthcare, and education. Despite its potential, current DHM simulations grapple with challenges like high computational costs, significant latency, low precision,
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· An example would be Step 1 of the process is executed by Operator A with a skill level S1, using machine M1, on day 1 of the week, or Step 1 is executed by Operator B with skill level S2 using machine M1 on day 2.. and so on for every possible combination of
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A digital twin is a virtual representation of an object or system designed to reflect a physical object accurately. It spans the object's lifecycle, is updated from real-time data and uses simulation, machine learning and reasoning to help make decisions. How does a digital twin work? The studied object—for example, a wind turbine—is
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· Ritto et al. presented a digital twin framework combining physics-based models and machine learning classifiers for dynamic structural damage detection, but it has limitations in identifying
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· An example would be Step 1 of the process is executed by Operator A with a skill level S1, using machine M1, on day 1 of the week, or Step 1 is executed by Operator B with skill level S2 using
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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
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Herein, digital twin modeling was identified as an enabling technology for machine tool intelligence based on a comparative study of the characteristics of machine tool
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· At present, the informatization level in the construction process of steel structures is relatively low. Meanwhile, digital twin technology, with better interactive features, provides a new development direction for the intelligent construction of steel structures. Therefore, this paper introduces the concept of a digital twin into the steel
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· The discovery of multiple-object phases such as assembly has not received enough attention from the literature, although being among the most common production steps. Indeed, with the sole exception of Lugaresi and Matta (2021b), the aforementioned papers do not specifically focus on model generation including the
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4 · A framework is proposed for generative models as a basis for digital twins or mirrors of structures. The proposal is based on the premise that deterministic models cannot account for the uncertainty present in most structural modeling applications. Two different types of generative models are considered here. The first is a physics-based
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Firstly, can be used as product development simulator at design phase. Secondly, it can be altered to training simulator for teaching future users of the product in use phase. Thirdly, is can be altered to digital twin of the product to be used for monitoring the machine operation during lifecycle.
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· Digital twin is a concept redefined with the emergence of Industry 4.0, reflecting the physical characteristics of a certain physical entity into its numerical/digital model in the cyber space. Machine Tool Digital Twin (MTDT) is the application of the digital twin concept on machine tools. MTDT enables thorough analysis of the physical
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· Digital impressions and handling of digital models: the future of Dentistry. October 2010. Dental Press Journal of Orthodontics 15 (5):18-22. DOI: 10.1590/S2176-94512010000500003. License. CC BY
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· 3.3. A brief overview of other similar concepts that preceded DT The concept of digitising and twinning are not new. Many similar concepts have preceded DT, however, for the reasons briefly described below, they differ. • Digital Shadow, Digital Model A Digital Model has only manual exchange of data and it does not showcase the
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· Combining digital twin with 3D computer vision, this paper defines a novel feature-level digital twin process model (FL-DTPM) by extracting machining features from model-based definition models. Firstly, a multi-dimensional FL-DTPM framework is defined by fusing on-site data, quality information, and process knowledge, where the synergistic
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· The Machine learning (ML) revolution is becoming established in oceanographic research, but its applications to emulate marine biogeochemical models are still rare. We pioneer a novel application of machine learning to emulate a highly complex physical-biogeochemical model to predict marine oxygen in the shelf-sea environment.
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Introduction. Digital twins are virtual replicas of real-world systems that accurately reflect the system’s behavior, with the goal of achieving functionalities like automatic fault diagnosis
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While less feature-rich informational Digital Twins may be viable, autonomous Digital Twins using methods of Machine Learning (ML) are unattainable for these companies due to the high complexity. With Model-Based Systems Engineering (MBSE), an approach was introduced to grasp this complexity using system models e.g., SysML-diagrams.
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· 11 Types of digital business models. 1. Advertising model (“Ad-supported free model”) The ad-supported model offers free services to users, with revenue coming from advertisers who pay to
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Machine tools digital twin(MTDT) is a derivative of DT in manufacturing and is considered to be the core component of the next generation of intelligent machine tools. This paper
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While less feature-rich informational Digital Twins may be viable, autonomous Digital Twins using methods of Machine Learning (ML) are unattainable for these companies due to the high complexity. With Model-Based Systems Engineering (MBSE), an approach was
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· Beyond Language Models: Byte Models are Digital World Simulators. Shangda Wu, Xu Tan, Zili Wang, Rui Wang, Xiaobing Li, Maosong Sun. Traditional deep learning often overlooks bytes, the basic units of the digital world, where all forms of information and operations are encoded and manipulated in binary format.
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· Improving the accuracy of the digital model is essential for the digitalization of the dental field. This study introduced a novel method of objective accuracy evaluation of digitized full dental arch
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The presented digital twin introduces a new type of digital twins, a “heterogeneous” digital twin that comprises simulation models and real software and hardware components of
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· Digital Model. A digital model is a virtual representation of a physical object, system, or process. It can have various forms, such as 3D models, computer-aided design (CAD) files, simulations, or mathematical algorithms. Digital models enable the visualisation, analysis, and manipulation of objects or systems in a digital environment,
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