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Bridge damage: Detection, IFC-based semantic enrichment and visualization

Thumbnail
2020
Preprint (40.90Mb)
Authors
Isailović, Dušan
Stojanovic, Vladeta
Trapp, Matthias
Richter, Rico
Hajdin, Rade
Döllner, Jürgen
Article (Accepted Version)
,
Elsevier
Metadata
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Abstract
Building Information Modeling (BIM) representations of bridges enriched by inspection data will add tremendous value to future Bridge Management Systems (BMSs). This paper presents an approach for point cloud-based detection of spalling damage, as well as integrating damage components into a BIM via semantic enrichment of an as-built Industry Foundation Classes (IFC) model. An approach for generating the as-built BIM, geometric reconstruction of detected damage point clusters and semantic-enrichment of the corresponding IFC model is presented. Multiview-classification is used and evaluated for the detection of spalling damage features. The semantic enrichment of as-built IFC models is based on injecting classified and reconstructed damage clusters back into the as-built IFC, thus generating an accurate as-is IFC model compliant to the BMS inspection requirements."
Keywords:
Damage detection / Building Information Modeling / 3D point clouds / Multiview classification / Bridge Management Systems
Source:
Automation in Construction, 2020, 112
Publisher:
  • Elsevier
Funding / projects:
  • Development of the method for the production of MEP design and construction documents compatible with BIM process and related standards (RS-36038)

DOI: 10.1016/j.autcon.2020.103088

ISSN: 0926-5805

WoS: 000526785600012

Scopus: 2-s2.0-85078194587
[ Google Scholar ]
51
20
URI
https://grafar.grf.bg.ac.rs/handle/123456789/1857
Collections
  • Катедра за управљање пројектима у грађевинарству
Institution/Community
GraFar
TY  - JOUR
AU  - Isailović, Dušan
AU  - Stojanovic, Vladeta
AU  - Trapp, Matthias
AU  - Richter, Rico
AU  - Hajdin, Rade
AU  - Döllner, Jürgen
PY  - 2020
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1857
AB  - Building Information Modeling (BIM) representations of bridges enriched by inspection data will add tremendous value to future Bridge Management Systems (BMSs). This paper presents an approach for point cloud-based detection of spalling damage, as well as integrating damage components into a BIM via semantic enrichment of an as-built Industry Foundation Classes (IFC) model. An approach for generating the as-built BIM, geometric reconstruction of detected damage point clusters and semantic-enrichment of the corresponding IFC model is presented. Multiview-classification is used and evaluated for the detection of spalling damage features. The semantic enrichment of as-built IFC models is based on injecting classified and reconstructed damage clusters back into the as-built IFC, thus generating an accurate as-is IFC model compliant to the BMS inspection requirements."
PB  - Elsevier
T2  - Automation in Construction
T1  - Bridge damage: Detection, IFC-based semantic enrichment and visualization
VL  - 112
DO  - 10.1016/j.autcon.2020.103088
ER  - 
@article{
author = "Isailović, Dušan and Stojanovic, Vladeta and Trapp, Matthias and Richter, Rico and Hajdin, Rade and Döllner, Jürgen",
year = "2020",
abstract = "Building Information Modeling (BIM) representations of bridges enriched by inspection data will add tremendous value to future Bridge Management Systems (BMSs). This paper presents an approach for point cloud-based detection of spalling damage, as well as integrating damage components into a BIM via semantic enrichment of an as-built Industry Foundation Classes (IFC) model. An approach for generating the as-built BIM, geometric reconstruction of detected damage point clusters and semantic-enrichment of the corresponding IFC model is presented. Multiview-classification is used and evaluated for the detection of spalling damage features. The semantic enrichment of as-built IFC models is based on injecting classified and reconstructed damage clusters back into the as-built IFC, thus generating an accurate as-is IFC model compliant to the BMS inspection requirements."",
publisher = "Elsevier",
journal = "Automation in Construction",
title = "Bridge damage: Detection, IFC-based semantic enrichment and visualization",
volume = "112",
doi = "10.1016/j.autcon.2020.103088"
}
Isailović, D., Stojanovic, V., Trapp, M., Richter, R., Hajdin, R.,& Döllner, J.. (2020). Bridge damage: Detection, IFC-based semantic enrichment and visualization. in Automation in Construction
Elsevier., 112.
https://doi.org/10.1016/j.autcon.2020.103088
Isailović D, Stojanovic V, Trapp M, Richter R, Hajdin R, Döllner J. Bridge damage: Detection, IFC-based semantic enrichment and visualization. in Automation in Construction. 2020;112.
doi:10.1016/j.autcon.2020.103088 .
Isailović, Dušan, Stojanovic, Vladeta, Trapp, Matthias, Richter, Rico, Hajdin, Rade, Döllner, Jürgen, "Bridge damage: Detection, IFC-based semantic enrichment and visualization" in Automation in Construction, 112 (2020),
https://doi.org/10.1016/j.autcon.2020.103088 . .

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