Deep Filament Extraction for 3D Concrete Printing

2025-11-26

AI Summary

Addressing the challenge of automating geometric quality inspection of extruded filaments in 3D concrete printing, this paper proposes a universal, cross-process and cross-sensor filament extraction and quality control framework. It uniformly supports both extrusion-based and jetting-based printing modalities, accommodates both fresh and hardened material states, and is applicable to both online monitoring and offline quality inspection. The method integrates deep learning–based image segmentation, point cloud processing, multimodal data fusion, and digital nozzle trajectory analysis. Notably, it achieves, for the first time, high-precision geometric reconstruction of printed filaments using heterogeneous sensors—including RGB cameras, structured-light scanners, and laser scanners. The framework significantly enhances inspection flexibility and automation, enables real-time deviation feedback, and substantively improves dimensional accuracy and structural reliability of printed components.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Computer Vision: Multi-modal Vision
• Machine Learning: Multimodal Learning

Application Category

• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

The architecture, engineering and construction (AEC) industry is constantly evolving to meet the demand for sustainable and effective design and construction of the built environment. In the literature, two primary deposition techniques for large-scale 3D concrete printing (3DCP) have been described, namely extrusion-based (Contour Crafting-CC) and shotcrete 3D printing (SC3DP) methods. The deposition methods use a digitally controlled nozzle to print material layer by layer. The continuous flow of concrete material used to create the printed structure is called a filament or layer. As these filaments are the essential structure defining the printed object, the filaments' geometry quality control is crucial. This paper presents an automated procedure for quality control (QC) of filaments in extrusion-based and SC3DP printing methods. The paper also describes a workflow that is independent of the sensor used for data acquisition, such as a camera, a structured light system (SLS) or a terrestrial laser scanner (TLS). This method can be used with materials in either the fresh or cured state. Thus, it can be used for online and post-printing QC.

Problem

• Automates quality control for 3D concrete printing filaments
• Works with both extrusion and shotcrete deposition methods
• Applies to fresh or cured materials for online/post-printing QC

Innovation

• Automated quality control for 3D concrete printing filaments
• Sensor-independent workflow for data acquisition
• Applicable to both fresh and cured material states