| DOI | Trouver le DOI : https://doi.org/10.1117/12.2660270 |
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| Auteur | Rechercher : Liu, Zheng; Rechercher : Blasch, Erik; Rechercher : Liao, Min1; Rechercher : Yang, Chunsheng2; Rechercher : Tsukada, Kazuhiko; Rechercher : Meyendorf, Norbert |
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| Éditeur | Rechercher : Meyendorf, Norbert G.; Rechercher : Singh, Ripi; Rechercher : Niezrecki, Christopher |
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| Affiliation | - Conseil national de recherches Canada. Aérospatiale
- Conseil national de recherches Canada. Technologies numériques
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| Format | Texte, Article |
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| Conférence | NDE 4.0, Predictive Maintenance, Communication, and Energy Systems: The Digital Transformation of NDE, March 12-17, 2023, Long Beach, United States |
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| Sujet | predictive maintenance; digital twin; information fusion; data modeling; analytic models; computing systems; analytics; computer simulations; data fusion; sensors |
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| Résumé | Digital twin engineering is a disruptive technology that creates a living data model of industrial assets. The living model will continually adapt to changes in the environment or operations using real-time sensory data as well as forecast the future of the corresponding infrastructure. A digital twin can be used to proactively identify potential issues with its real physical counterpart, allowing the prediction of the remaining useful life of the physical twin by leveraging a combination of physics-based models and data-driven analytics. The digital twin ecosystem comprises sensor and measurement technologies, industrial Internet of Things, simulation and modeling, and machine learning. This paper will review the digital twin technology and highlight its application in predictive maintenance applications. |
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| Date de publication | 2023-04-25 |
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| Maison d’édition | SPIE |
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| Dans | |
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| Série | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | ba32c5cb-6056-45f9-bd00-044b0a9483f9 |
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| Enregistrement créé | 2024-07-11 |
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| Enregistrement modifié | 2024-07-11 |
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