| Autre titre | Case study on the application of microstructural features extracted by a convolutional neural network for cold spray of aluminum alloys |
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| Téléchargement | - Voir la version de l’auteur : Case study on the application of microstructural features extracted by convolutional neural network for cold spray of aluminum alloys (PDF, 1.4 Mio)
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| DOI | Trouver le DOI : https://doi.org/10.31399/asm.cp.itsc2023p0009 |
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| Auteur | Rechercher : Tu, Siyu1; Rechercher : Vo, Phuong1 |
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| Affiliation | - Conseil national de recherches du Canada. Automobile et les transports de surface
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| Format | Texte, Article |
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| Conférence | ITSC 2023, May 22-25, 2023, Québec City, Canada |
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| Résumé | The use of process-microstructure-property relationships for cold spray can significantly reduce application development cost and time compared to legacy trial and error strategies. However, due to the heterogeneous microstructure of a cold spray deposit, with (prior) particle boundaries outlining consolidated splats (deformed particles) in the as-spray condition, the use of automated analysis methods is challenging. In this work, we demonstrate the utility of quantitative data developed from a convolutional neural network (CNN) for feature extraction of cold spray microstructures. Specifically, the power of CNN is harnessed to automatically segment the deformed particles, which is hardly accessible at scale with traditional image processing techniques. Deposits produced with various processing conditions are evaluated with metallography. Parameters related to particle morphology such as compactness are also quantified and correlated to strength. |
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| Date de publication | 2023-05-22 |
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| Maison d’édition | ASM International |
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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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| Numéro du CNRC | NRC-AST-2022-2023-19 |
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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 | e2da72b1-56c0-4b17-9b97-d0d27a64679e |
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| Enregistrement créé | 2023-08-28 |
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| Enregistrement modifié | 2023-08-28 |
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