Building information modeling and non-destructive testing

Sarah Hammerschick, Sommersemester 19

1. Building information modeling (BIM)

Building Information Modelling is a method to extend a geometrical computer model of a building structure with functional data from planning, execution and utilization.^[1]  This data can be visualized trough a Computer Aided Design Model in order to present dependencies and context.^[1] The basis for this model can be a construction plan, a photogrammetry scan, a 3D surface recording by laser scanner or an infrared depth recording.  One aim of BIM is to integrate non-destructive testing results automatically into a full-building reconstruction or building information model wherever significant damage appear.^[2]

2. Non-destructive testing (NDT) in Civil Engineering

To guarantee the quality of execution on the construction site and estimate the remaining lifespan of the building, the analysis of the actual state of and damage to the building is very important.^[1]  Characteristic Values are electrochemical potential, concrete cover, carbonation depth, chloride profiles, cracks, delamination and corrosion damage of the reinforcement.^[3] For this purpose, there are a couple of non-destructive testing methods, such as ultrasonic analysis, potential field measurement, impact-echo and microwave method.

3. Spatial Mapping

There are various non-destructive testing methods, however only a few can automatically collect larger measuring ranges on concrete components and integrate this information into a building information model.  In order to collect such volumes of data and non-destructive testing results, automatic measurement and mapping methods can be quite helpful.^[1] The selection of a suitable coordinate system, inherently consistent and extend over the entire building, is very important for an automatic measurement and mapping system.^[1]  In some cases, this coordinate system must be adapted to sub coordinate systems for individual areas or construction elements. Origin, axis direction, and axis unit should be previously defined.^[1] Distributed survey points are a great help to calibrate the given coordinate system.^[1] Fixed, electronically readable tags can provide additional information about the relationship between the main- and subsystem.^[1]

4. Examples for automatic measurement and mapping systems

4.1 Unmanned Aircraft Systems

An optical shot is taken to get an overview and locate the cracks. To take these shots and monitor buildings a Vertical take-off and Landing (VTOL) is an option.^[4] The navigation of the VTOL is mostly done by GPS, with additional support from a 3D magnetic sensor.^[2] The visual building inspection via an unmanned aircraft vehicle is divided into two steps: data acquisition during the in-flight and the digital post processing.^[2] After the optical shot, algorithms look for similar picture content structures and pattern recognition is used to combine the pictures through matching points.^[1] The generated pictures are “stitched” together to obtain a full 2D image where damage and cracking can be spotted.^[2]  Algorithms have been programmed to automatically detect cracks in high-resolution areas down to the millimeter range.^[2] There are two ways highlighting and extracting the cracks

• Adding additional color value
• Edge detection bases upon Gaussian blur^[2]

4.2 Automatic multisensory data collection: BETOSCAN

BETOSCAN is a sensor equipped robotic system that is able to navigate autonomously over large concrete surfaces automatically recording all relevant data in one-step:^[3]

• Optical analysis (position of cracks and damaged zones)
• Microwaves (humidity distribution)
• Potential mapping (corrosion probability)
• Eddy current method + radar ( reinforcement location and cover)
• Ultrasonic ( voids, thickness, crack depth)
• Air temperature and concrete temperature
• Rel. humidity
• Concrete resistance

The 270 ° scanner moves autonomously over horizontal surfaces, generating a digital environmental map.^[3] This map contains a common coordinate system where every data package is saved with the exact position. The map can be used for a detailed picture or evaluation model in order to predict the lifecycle costs or construction measures.^[3]

4.3 RABIT

The autonomous robot RABIT was designed to detect reinforcing corrosion, delamination and decreased concrete quality on bridges roadway slaps.^[3]  RABIT provides sensors for radar, ultrasonic surface waves, impact echo and electrical resistance measurement. The RABIT moves completely autonomous over the surface, due to a Global Positioning System (GPS). A software for online data analysis and data fusion generates a map where all the damaged spots are collected.^[1] The visualization software presents all information in a common three-dimensional space in order to mark the different degrees of damage. ^[1]

4.4 Ground penetration radar and development of a 3D model

The Ground Penetration Radar (GPR) measurements can be used to create a 3D visualization.^[5] In order to create a 3D Representation out of the analyzed georadar data it is first converted into a JPG file with georeferences. Those Layers with height information where transferred to Polylines. This polylines where transformed to a 3D point cloud. This cloud is converted to a mesh generation, which leads to a 3D visualization.^[5]

5. combined scale-independent visualization

For non-destructive testing in civil engineering it is important to capture multiscale information and put them into context via a virtual building model. Automated measuring and imaging systems must be integrated into a structure to be effectively usable for quality management.^[1] One way is a multiscale simulation where NDT measurements and the optical building recording are overlaid in a CAD Modell.^[1] The result is a virtual and walkable model in order to present data by different scales in order to assess the context.^[1]  Automated imaging systems simplify the process of measurement setup and execution of measurement tasks. The standardized results are more easily accessible for further integration into a building
information Model.

6. Literature

^[1]  Schickert, Martin: Automatisierte Abbildungssysteme, Visualisierung und Wege zu einem Qualitätsmanagement, Fachtagung Bauwerksdiagnose 2016 Vortrag 4

^[2] Eschman, C., Kuo C.-M., C.-H. Kuo: unmanned aircraft systems for remote building inspection and Monitoring. 6^th European Workshop on Structural Health Monitoring- Th.2.B.1.

^[3]  Reichling, K., Raupach M., Wiggenhauser H.: BETOSCAN – Robot controlled non-destructive diagnosis of reinforced concrete decks. Non-Destructive Testing in Civil Engineering. Nantes. France. 2009

^[4]  Kurz, Jochen: Das virtuelle Bauwerk – Kombinierte skalenübergreifende Visualisierung von ZfP-Bau Ergebnissen, Fachtagung Bauwerksdiagnose 2012-Vortrag 18

^[5] P. Agrafiotiss, K.Lampropoulos, A.Georgopoulus: 3D modelling the invisible using ground penetrating radar, The international archives of the Photogrammetry, Remote sensing and spatial information sciences, Volume XLII-2W3, 2017 3D Virtual Reconstruction and Visualization of Complexe Architectures, 1 -3 march 2017, Nafplio, Greece