About this Abstract |
Meeting |
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
|
Symposium
|
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
|
Presentation Title |
Fully Registered Overhang X4 Data from Additive Manufacturing Metrology Testbed (AMMT): Multi-Sensor Datasets Integration |
Author(s) |
Zhuo Yang, Yan Lu, Ho Yeung, Brandon Lane |
On-Site Speaker (Planned) |
Zhuo Yang |
Abstract Scope |
This presentation details a comprehensive dataset integrating multiple raw datasets from the National Institute of Standards and Technology (NIST) Additive Manufacturing Metrology Testbed. The data originates from an experiment involving four identical overhang parts. It encompasses five raw data types: digital commands, real position and laser power, melt pool monitoring (MPM) images, layerwise images, and X-ray computed tomography. The raw data underwent processing to remove noise and extract features. For instance, MPM images were used to extract melt pool geometric features using various methods. Subsequently, extracted features from each dataset were spatially and temporally registered to the machine's coordinate system. Fully registered data comprises millions of data points with dozens features. The document describes the data processing, feature extraction, and data registration techniques employed. It details existing uncertainties encountered during the integration process. The data is presently undergoing NIST's data publishing process. Sample data will be released during the conference. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |