Published December 20, 2023 | Version v1
Dataset Open

Dataset of Hyperspectral Melt Pool Signatures and Thermal Anomalies in DED of 316L steel

  • 1. ROR icon Vrije Universiteit Brussel


Description of the dataset
The dataset includes in-situ melt pool signatures (hyperspectral NIR images) during the Directed Energy Deposition of 316L steel for several classes of thermal anomalies. Thermal anomalies were created during the process by varying the scanning speed.

Samples were printed on the MiCLAD machine at the Vrije Universiteit Brussel (Belgium).

Process and acquisition parameters:

  • Hardware:
    • Machine: MiCLAD (Vrije Universiteit Brussel)
    • Laser: High-YAG BIMO 1064nm, 2.55mm fibre, flat-top
    • Nozzle: Harald-Dickler HighNo 4.0
  • Process parameters:
    • Laser power: 600 W
    • Scanning speed: 500/700/900/1100/1300 mm/min
    • Powder: 316L 45-105 um
    • Powder flow rate: 3.5 g/m
    • Layer thickness: 0.2 mm
  • Image characteristics:
    • Camera: 3D-One Avior AX-M25NIR
    • Hyperspectral filter layout: 5x5 (25 wavelengths per image)

Description of the files

  • CSV dataset (hyperspectral_nir_meltpool_dataset.csv): List of filename, sample, label, time (ms), X and Z position (mm) and local scanning speed (mm/min) for all melt pool signatures. Thermal anomalies are labelled accordingly:
    • 0 : baseline
    • 1 : edge
    • 2 : underheat
    • 3 : strong underheat
    • 4 : overheat
    • 5 : strong overheat
  • Melt pool signatures (hyperspectral_nir_meltpool_images_*.zip): Raw .tif thermal images of the melt pool taken in-situ. The raw images must debayered to retrieve the spectral information, see the Python function and example script. 
  • Python debayer function ( Debayering function to retrieve the spectral information from the raw images. 



Files (43.0 GB)

Name Size Download all
3.2 kB Download
38.8 MB Preview Download
11.4 GB Preview Download
6.0 GB Preview Download
12.1 GB Preview Download
13.5 GB Preview Download
1.8 kB Preview Download