nVisDa

Structures for consistent building inspection
with digital images and data analytics


Problem

The foundation of safe use and long-term maintenance of transport infrastructure structures such as bridges and tunnels is structure inspection during regular inspections with the aim of detecting damage. However, conventional "hands-on" structural inspection is time-, cost- and personnel-intensive and does not allow automated analysis of the collected condition data. The automated recording of large structures and condition analysis with digital imaging techniques has great potential in structure maintenance, but has not yet been systematically applied in practice.

Project objective

The use of drones and other sensor platforms and the application of digital data analysis can efficiently generate high-quality information about the geometry and condition of structures. This project aims to lay the foundation for the practical introduction of these digital methods in building maintenance by preparing and characterizing the essential process steps and compiling them in a catalog of requirements and guidelines. 

Implementation

In addition to the systematic investigation and definition of the requirements for the acquisition and evaluation of image data, the modeling of heterogeneous data sets taking into account the complete workflow is a further focus. Digital data includes e.g. images, 3D point clouds and models as well as extracted damage information. The digital condition data of the structures are to be generated systematically and highly automated and are to be kept in digital twins with BIM reference. Taking into account the developed specifications, raw data will be recorded on a reference bridge structure and the data will be continuously generated and made available for all process steps of the image-based digital preservation of structures.

Project duration

     11/2020 – 04/2021

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