Abstract
Digital three-dimensional (3D) scanning is a cutting-edge metrology method that can digitally reconstruct surface topography with high precision and accuracy. Such metrology can help traditional manufacturing processes evolve into a smart manufacturing paradigm, which can ensure product quality by automated sensing and control. However, due to limitations with the spatial resolution, scanning speed, and size of the focusing area, commercially available systems cannot be directly used for in-process monitoring in smart manufacturing. For example, a metal 3D printer requires a scanner with second-level sensing, micron-level spatial resolution, and a centimeter-scale scanning region. Among the 3D scanning technologies, structured light 3D scanning can meet the scanning speed criteria but not the spatial resolution and scanning region criteria. This work addresses these challenges by reducing the field of view of a structured light scanner system while increasing the image sensor pixel resolution. Improvements to spatial resolution and accuracy are achieved by establishing hardware selection criteria, integrating the proper hardware, designing a scale-appropriate calibration target, and developing noise reduction procedures during calibration. An additively manufactured Ti-6Al-4V part was used to validate the effectiveness of the proposed 3D scanner. The scanning result shows that both melt pool geometry and overall shape can be clearly captured. In the end, the scanning accuracies of the proposed scanner and a professional-grade commercial scanner are validated with a nanometer-level accuracy white light interferometer using high-density point cloud data. Compared to the commercial scanner, the proposed scanner improves the spatial resolution from 48 to 5 μm and the accuracy from 108.5 to 0.5 μm. Compared to the white light interferometer, the proposed scanner improves the scanning and processing speed from 2 to 20 s.
Highlights
1.1 BackgroundIn advanced manufacturing, automatic quality control is a key enabler for defect detection and mitigation based on sensor technologies
The 3D surface topological information can be obtained by 3D scanning, which is a group of sensor techniques that subvert the traditional point-to-point measurement by providing 3D point cloud data to evaluate the geometrical and dimensional quality of the manufactured parts
This paper aims to design and implement a new structured light 3D scanner (SLS) that can meet the in-process monitoring needs for metal Additive manufacturing (AM)
Summary
1.1 BackgroundIn advanced manufacturing, automatic quality control is a key enabler for defect detection and mitigation based on sensor technologies. The 3D surface topological information can be obtained by 3D scanning, which is a group of sensor techniques that subvert the traditional point-to-point measurement by providing 3D point cloud data to evaluate the geometrical and dimensional quality of the manufactured parts. These techniques have already been applied to some industries such as construction, entertainment, and medical instruments[4,5,6]. Their use for online process monitoring and control in advanced manufacturing is very limited. 20 to 30 pairs of images are taken for the calibration target at different angles and positions and used to calculate the spatial relationship between the two cameras
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