WelDX - data and quality standards for welding research data#
Scientific welding data covers a wide range of physical domains and timescales and are measured using various different sensors. Complex and highly specialized experimental setups at different welding institutes complicate the exchange of welding research data further.
The WelDX research project aims to foster the exchange of scientific data inside the welding community by developing and establishing a new open source file format suitable for the documentation of experimental welding data and upholding associated quality standards. In addition to fostering scientific collaboration inside the national and international welding community an associated advisory committee will be established to oversee the future development of the file format. The proposed file format will be developed with regard to current needs of the community regarding interoperability, data quality and performance and will be published under an appropriate open source license. By using the file format objectivity, comparability and reproducibility across different experimental setups can be improved.
The project is under active development by the Welding Technology division at Bundesanstalt für Materialforschung und -prüfung (BAM).
WelDX provides several Python API to perform standard tasks like experiment design, data analysis, and experimental data archiving.
Define measurement chains with all involved devices, error sources, and metadata annotations.
Handle complex coordinate transformations needed to describe the movement of welding robots, workpieces, and sensors.
Planing of welding experiments.
convenient creation of ISO 9692-1 welding groove types.
Plotting routines to inspect measurement chains, workpieces (planned and welded).
Analysis functions for standard measurements like track energy, welding speed to fill an ISO groove, and more to come.
The ultimate goal of this project is to store all information about the experiment in a single file. We choose the popular ASDF format for this task. This enables us to store arbitrary binary data, while maintaining a human readable text based header. All information is stored in a tree like structure, which makes it convenient to structure the data in arbitrary complex ways.
The ASDF format and the provided extensions for WelDX types like
workpiece information (used alloys, geometries)
welding process parameters (GMAW parameters)
coordinate systems (robot movement, sensors)
enables us to store the whole experimental pipeline performed in a modern laboratory.
We seek to provide a user-friendly, well documented programming interface. All functions and classes in WelDX have attached documentation about the involved parameters (types and explanation), see API docs. Further we provide rich Jupyter notebook tutorials about the handling of the basic workflows.
All involved physical quantities used in
weldx (lengths, angles,
voltages, currents, etc.) should be attached with a unit to ensure
automatic conversion and correct mathematical handling. Units are being
used in all standard features of WelDX and are also archived in the ASDF
files. This is implemented by the popular Python library Pint, which flawlessly handles
the creation and conversion of units and dimensions.
Recommendations for an Open Science approach to welding process research data. Fabry, C., Pittner, A., Hirthammer, V. et al. Weld World (2021). https://doi.org/10.1007/s40194-021-01151-x
The WelDX package can be installed using conda or mamba package manager
from the Conda-Forge channel. These managers originate from
the freely available Anaconda Python stack. If you do not have
Anaconda or Miniconda installed yet, we ask you to install
Miniconda-3. Documentation for the installation procedure can be
After this step you have access to the conda command and can proceed to
installing the WelDX package.
conda install weldx weldx_widgets -c conda-forge
The package is also available on pypi.
pip install weldx weldx-widgets
The full documentation is published on readthedocs.org. Click on one of the following links to get to the desired version:
This research is funded by the Federal Ministry of Education and Research of Germany under project number 16QK12.