A BIM Based Framework for Damage Segmentation, Modeling, and Visualization Using IFC
- Paper-based data acquisition and manual transfer between incompatible software or data formats during inspections of bridges, as done currently, are time-consuming, error-prone, cumbersome, and lead to information loss. A fully digitized workflow using open data formats would reduce data loss, efforts, and the costs of future inspections. On the one hand, existing studies proposed methods toPaper-based data acquisition and manual transfer between incompatible software or data formats during inspections of bridges, as done currently, are time-consuming, error-prone, cumbersome, and lead to information loss. A fully digitized workflow using open data formats would reduce data loss, efforts, and the costs of future inspections. On the one hand, existing studies proposed methods to automatize data acquisition and visualization for inspections. These studies lack an open standard to make the gathered data available for other processes. On the other hand, several studies discuss data structures for exchanging damage information among different stakeholders. However, those studies do not cover the process of automatic data acquisition and transfer. This study focuses on a framework that incorporates automatic damage data acquisition, transfer, and a damage information model for data exchange. This enables inspectors to use damage data for subsequent analyses and simulations. The proposed framework shows the potentials for a comprehensive damage information model and related (semi-)automatic data acquisition and processing.…
Dokumentart: | Artikel (Wissenschaftlicher) |
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Verfasserangaben: | Mathias ArtusORCiDGND, Mohamed Said Helmy AlabassyORCiD, Prof. Dr.-Ing. Christian KochORCiDGND |
DOI (Zitierlink): | https://doi.org/10.3390/app12062772Zitierlink |
URN (Zitierlink): | https://nbn-resolving.org/urn:nbn:de:gbv:wim2-20220314-46059Zitierlink |
URL: | https://www.mdpi.com/2076-3417/12/6/2772 |
Titel des übergeordneten Werkes (Englisch): | Applied Sciences |
Verlag: | MDPI |
Verlagsort: | Basel |
Sprache: | Englisch |
Datum der Veröffentlichung (online): | 08.03.2022 |
Datum der Erstveröffentlichung: | 08.03.2022 |
Datum der Freischaltung: | 14.03.2022 |
Veröffentlichende Institution: | Bauhaus-Universität Weimar |
Institute und Partnereinrichtugen: | Fakultät Bauingenieurwesen / Professur Intelligentes Technisches Design |
Jahrgang: | 2022 |
Ausgabe / Heft: | volume 12, issue 6, article 2772 |
Seitenzahl: | 24 |
Erste Seite: | 1 |
Letzte Seite: | 24 |
Freies Schlagwort / Tag: | OA-Publikationsfonds2022 Bridge; Building Information Modeling; Damage Segmentation; Inspection; Machine Learning |
GND-Schlagwort: | Building Information Modeling; Brücke; Inspektion; Maschinelles Lernen; Bildverarbeitung |
DDC-Klassifikation: | 600 Technik, Medizin, angewandte Wissenschaften / 620 Ingenieurwissenschaften / 624 Ingenieurbau |
BKL-Klassifikation: | 50 Technik allgemein / 50.16 Technische Zuverlässigkeit, Instandhaltung |
Open Access Publikationsfonds: | Open-Access-Publikationsfonds 2022 |
Lizenz (Deutsch): | Creative Commons 4.0 - Namensnennung (CC BY 4.0) |