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TACK project: Tunnel Automatic CracK monitoring using deep learning and photogrammetry
Sapienza University of Rome, DICEA, Rome, Italy.ORCID iD: 0000-0003-4765-0281
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Concrete Structures.ORCID iD: 0000-0001-8375-581X
avanelli, Roberta Sapienza Univ Rome, Geodesy & Geomat Div, DICEA, I-00184 Rome, Italy..ORCID iD: 0000-0001-5540-6241
Sapienza Univ Rome, Geodesy & Geomat Div, DICEA, I-00184 Rome, Italy.ORCID iD: 0000-0002-0592-6182
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2022 (English)In: Earth Observation for Environmental Monitoring 41st EARSeL Symposium, Paphos, Cyprus, 13-16 September 2022, 2022Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Crack detection and measurement are standard procedures during infrastructure inspections all over the world. Traditionally, infrastructures are only visually inspected. To accomplish this, tunnels must be closed and inspections are carried out during the night to minimize infrastructure downtime. Also, the limited time and the length of the system make it impossible to accurately inspect tunnels which increases the risk that cracks are not detected. Recently, inspections have been carried out using semi-automatic methods where a mobile mapping equipment is used to capture the scene and reconstruct the 3D model (the socalled digital twin) of tunnels using geomatics sensors (visible and infrared cameras, LiDAR, IMU). Then, the digital twin and the images are manually analysed to find cracks and mark their extent. Due to the large amount of data, the method is time-consuming, inefficient and affected by errors. The aim of this work is to improve efficiency and accuracy of inspections.

Place, publisher, year, edition, pages
2022.
Keywords [en]
Infrastructure monitoring, Digital twins, Photogrammetry, Deep learning
National Category
Infrastructure Engineering
Research subject
Geodesy and Geoinformatics, Geoinformatics; Civil and Architectural Engineering, Concrete Structures
Identifiers
URN: urn:nbn:se:kth:diva-317440OAI: oai:DiVA.org:kth-317440DiVA, id: diva2:1694814
Conference
Earth Observation for Environmental Monitoring 41st EARSeL Symposium, Paphos, Cyprus, 13-16 September 2022
Projects
TACK - Tunnel Automatic CracK Detection
Funder
EU, Horizon 2020, 101012456
Note

QC 20220928

Available from: 2022-09-12 Created: 2022-09-12 Last updated: 2024-01-18Bibliographically approved

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Sjölander, AndreasNascetti, Andrea

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