Digital representation of as-damaged reinforced concrete bridges
Апстракт
Inspection of bridges has been a standard assessment procedure for decades. Its purpose
is to identify and record all defects of the bridge structure. Normally used inspection
techniques are rather simple, mainly relying on visual assessment. This dissertation
proposes an improvement of concrete bridge inspection in terms of visual data acquisition,
damage identification and digital representation of the bridge with identified damages.
Instead of depending strictly on the human eye, photogrammetrically obtained 3D point
clouds are used to identify and extract concrete damage features. As the most
comprehensive substitute for the old-fashioned inspection report, Bridge Information
Model (BrIM) is used as an inventory and inspection data repository. An Industry
Foundation Classes (IFC) semantic enrichment framework is proposed to inject the
extracted and reconstructed damage features into the as-is IFC model.
After the general data model for damage description and its IFC repr...esentation are
established, the method for generating the as-is IFC model of the bridge is proposed.
Damage is identified as a deviation of the as-is geometry, represented by the 3D point
cloud, from the as-built geometry, represented by BrIM.
Geometric and semantic enrichment of the IFC model is achieved by injecting the
reconstructed 3D meshes representing damaged regions and corresponding BMS catalogbased
damage information. The proposed method uses Constructive Solid Geometry
(CSG) Boolean operations to geometrically enrich the IFC geometry elements, which align
with corresponding damage regions from the as-is point cloud. Damage information (e.g.,
type, extent, and severity) is structured so that it complies to the BMS data structure.
Finally, the proposed data model, damage identification, feature extraction, and semantic
enrichment method are validated in the presented case study.
Кључне речи:
Reinforced concrete bridge / Damage / Building Information Modeling / Bridge Information Modeling / Industry Foundation Classes / 3D Point Cloud / Bridge Management System / Unmanned Aerial VehicleИзвор:
2020Издавач:
- University of Belgrade Faculty of Civil Engineering
Финансирање / пројекти:
- Развој методе израде пројектне и извођачке документације инсталационих мрежа у зградама компатибилне са BIM процесом и релевантним стандардима (RS-MESTD-Technological Development (TD or TR)-36038)
Колекције
Институција/група
GraFarTY - THES AU - Isailović, Dušan PY - 2020 UR - https://grafar.grf.bg.ac.rs/handle/123456789/2170 AB - Inspection of bridges has been a standard assessment procedure for decades. Its purpose is to identify and record all defects of the bridge structure. Normally used inspection techniques are rather simple, mainly relying on visual assessment. This dissertation proposes an improvement of concrete bridge inspection in terms of visual data acquisition, damage identification and digital representation of the bridge with identified damages. Instead of depending strictly on the human eye, photogrammetrically obtained 3D point clouds are used to identify and extract concrete damage features. As the most comprehensive substitute for the old-fashioned inspection report, Bridge Information Model (BrIM) is used as an inventory and inspection data repository. An Industry Foundation Classes (IFC) semantic enrichment framework is proposed to inject the extracted and reconstructed damage features into the as-is IFC model. After the general data model for damage description and its IFC representation are established, the method for generating the as-is IFC model of the bridge is proposed. Damage is identified as a deviation of the as-is geometry, represented by the 3D point cloud, from the as-built geometry, represented by BrIM. Geometric and semantic enrichment of the IFC model is achieved by injecting the reconstructed 3D meshes representing damaged regions and corresponding BMS catalogbased damage information. The proposed method uses Constructive Solid Geometry (CSG) Boolean operations to geometrically enrich the IFC geometry elements, which align with corresponding damage regions from the as-is point cloud. Damage information (e.g., type, extent, and severity) is structured so that it complies to the BMS data structure. Finally, the proposed data model, damage identification, feature extraction, and semantic enrichment method are validated in the presented case study. PB - University of Belgrade Faculty of Civil Engineering T1 - Digital representation of as-damaged reinforced concrete bridges UR - https://hdl.handle.net/21.15107/rcub_grafar_2170 ER -
@phdthesis{ author = "Isailović, Dušan", year = "2020", abstract = "Inspection of bridges has been a standard assessment procedure for decades. Its purpose is to identify and record all defects of the bridge structure. Normally used inspection techniques are rather simple, mainly relying on visual assessment. This dissertation proposes an improvement of concrete bridge inspection in terms of visual data acquisition, damage identification and digital representation of the bridge with identified damages. Instead of depending strictly on the human eye, photogrammetrically obtained 3D point clouds are used to identify and extract concrete damage features. As the most comprehensive substitute for the old-fashioned inspection report, Bridge Information Model (BrIM) is used as an inventory and inspection data repository. An Industry Foundation Classes (IFC) semantic enrichment framework is proposed to inject the extracted and reconstructed damage features into the as-is IFC model. After the general data model for damage description and its IFC representation are established, the method for generating the as-is IFC model of the bridge is proposed. Damage is identified as a deviation of the as-is geometry, represented by the 3D point cloud, from the as-built geometry, represented by BrIM. Geometric and semantic enrichment of the IFC model is achieved by injecting the reconstructed 3D meshes representing damaged regions and corresponding BMS catalogbased damage information. The proposed method uses Constructive Solid Geometry (CSG) Boolean operations to geometrically enrich the IFC geometry elements, which align with corresponding damage regions from the as-is point cloud. Damage information (e.g., type, extent, and severity) is structured so that it complies to the BMS data structure. Finally, the proposed data model, damage identification, feature extraction, and semantic enrichment method are validated in the presented case study.", publisher = "University of Belgrade Faculty of Civil Engineering", title = "Digital representation of as-damaged reinforced concrete bridges", url = "https://hdl.handle.net/21.15107/rcub_grafar_2170" }
Isailović, D.. (2020). Digital representation of as-damaged reinforced concrete bridges. University of Belgrade Faculty of Civil Engineering.. https://hdl.handle.net/21.15107/rcub_grafar_2170
Isailović D. Digital representation of as-damaged reinforced concrete bridges. 2020;. https://hdl.handle.net/21.15107/rcub_grafar_2170 .
Isailović, Dušan, "Digital representation of as-damaged reinforced concrete bridges" (2020), https://hdl.handle.net/21.15107/rcub_grafar_2170 .