by Sina Akhbari, Peter Kinnell, Liam Whyte, Andy Gleadall, Richard Busswell, Sergio Cavalaro
Abstract
Precise real-time control of material behavior is critical for extrusion-based 3D concrete printing, where yield stress at the nozzle exit governs layer stability and print quality. Conventional offline tests fail to capture the evolving rheology during printing. This study presents a novel inline vision-based framework for monitoring slug formation at the nozzle, enabling non-invasive estimation of material behavior under extrusion conditions. The proposed method combines robust extrinsic camera calibration with a dedicated image processing pipeline, incorporating invariant template matching, adaptive thresholding, contour-based axis fitting, and volumetric estimation based on solid of revolution principles. A high-speed imaging setup is used to demonstrate the system’s ability to track slug formation and analyze trends under varying pump speeds. Results illustrate the method’s capability to detect process transitions and flow regimes, highlighting its potential as a foundation for real-time quality monitoring and closed-loop control in digital concrete fabrication.
Video presentation
Presenting author
| Name: Affiliation: Email: | Sina Akhbari Loughborough University, UK s.akhbari@lboro.ac.uk | |
