Intelligent digitization of existing bridges with mdfBIM+: Through automation to a digital twin
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Artificial intelligence meets innovation: Digital building models based on the BIM method (Building Information Modeling) are an essential prerequisite for efficient and sustainable maintenance management of the transport infrastructure. Under the direction of the ICoM, the Institute for Construction Management, Digital Engineering and Robotics in Construction at RWTH Aachen University, an interdisciplinary consortium from science and industry wants to enable the efficient (partly) automated creation of digital twins for the transport infrastructure.
The structural maintenance of approx. 25,000 railway bridges and almost 40,000 bridges in the federal trunk road network requires a reliable digital basis in the form of digital building models. So far, however, these can only be generated with a great deal of time and resources. Existing inventory documentation is mostly in analogue form and is often not up-to-date. The result: Future-oriented, digitized and thus efficient building maintenance is made extremely difficult for operators of infrastructure systems. The semi-automated creation of digital building models can help here.
Via multi-data fusion to the digital twin of infrastructure buildings
“Digital building models are the essential basis for efficient maintenance of our transport infrastructure. If we can generate this automatically by merging current scan data and existing inventory documentation, we will take a big step towards digital maintenance and thus towards a sustainable infrastructure," emphasizes Professor Katharina Klemt-Albert, who is responsible for the research project.
To create the model, the researchers use geometric measurement data (point clouds and photogrammetry) on the one hand and existing building documentation of the infrastructure structures on the other. The geometric measurement data is recorded from the air by drone in connection with special LIDAR and camera systems and interpreted with the help of AI-based algorithms. At the same time, the existing inventory documents are evaluated with regard to their reliability and merged with the geometric data. This creates a digital representation of the transport infrastructure as a so-called digital twin. This is of great importance for future-oriented and digital maintenance management. The mdfBIM+ project thus makes a direct contribution to the availability and improvement of mobility in society.
The research project promotes digitization and competence in dealing with key technologies of the future. In the context of the project, new jobs will be created and thus the structural change of the coal regions towards an innovation location will be supported.
“About the mFUND of the BMVI:
As part of the mFUND innovation initiative, the BMVI has been funding research and development projects relating to data-based digital applications for Mobility 4.0 since 2016. In addition to financial support, the mFUND supports networking between actors from politics, business and research as well as access to the mCLOUD data portal with various event formats. You can find more information at www.mfund.de.”
Facts about the project
- Project: mdfBIM+
- Topic: Intelligent digitalization of existing bridges through automation to the digital twin
- Project duration: 12/01/2021 to 11/30/2024 (3 Years)
- Type of project: Digitalization in the bridge stock
- Funder: mFUND
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Project consortium:
RWTH Aachen University, ICoM - Institute for Construction Management, Digital Engineering and Robotics in Construction
Albert-Ludwigs-Universität Freiburg, Institut für Nachhaltige Technische Systeme (INATECH), Freiburg
Technical University Dresden, Institute for solid construction (IMB)
albert.ing GmbH
Galileo IP GmbH
customQuake GmbH
Deutsche Bahn AG (Assoziierter Partner)
Autobahn GmbH (Assoziierter Partner)
Bavarian State Ministry for Housing, Construction and Transport (Associate Partner) - Project Leader: Univ.-Prof. Dr.-Ing. Katharina-Klemt-Albert
- Contact person ICoM: Jan-Iwo Jäkel