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Intel_Robotic_Welding_Multimodal_Dataset

Modalities:
Audio
Video
Time-series
ArXiv:
Tags:
audio
video
timeseries
image
robotics
welding
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Dataset Card for the Intel Robotic Welding Multimodal Dataset

This dataset was collected to enable multimodal welding defect detection research. The dataset contains over 4000 annotated samples and was collected in an automotive production floor setting in collaboration with a supplier with access to such facilities. Each sample contains a video, associated audio, a time-series from welding sensors, and five post-weld images for a particular weld. A separately licensed, higher-fidelity, version is available for purchase.

License

Intel Research Use License Agreement. See below.

Reference

For comprehensive details, please consult our publication. Should you utilize our dataset in your research, we kindly request that you cite our paper.

@misc{stemmer2024unsupervisedweldingdefectdetection,
      title={Unsupervised Welding Defect Detection Using Audio And Video}, 
      author={Georg Stemmer and Jose A. Lopez and Juan A. Del Hoyo Ontiveros and Arvind Raju and Tara Thimmanaik and Sovan Biswas},
      year={2024},
      eprint={2409.02290},
      archivePrefix={arXiv},
      primaryClass={cs.RO},
      url={https://arxiv.org/abs/2409.02290}, 
}

Equipment List

  • Welding Robot: OTC AII-V6 6-axis arc welding robot.
  • Camera: KML welding camera.
  • Microphone: Earthworks SR314 high-bandwidth microphones.

Dataset Structure

The dataset contains subdirectories for 236 welding sessions. Each welding session subdirectory contains sample subdirectories with each one containing AVI, FLAC, and CSV files and an images directory containing 5 post-weld images.

Data Format

  • Audio Recording: 1 channel at 16 KHz sampling rate saved in lossless FLAC format.
  • Video Recording: Nominal 30 FPS, saved in AVI format.
  • Camera Position: Attached to the welder arm, approximately 200mm from the torch.
  • Microphone Position: Attached to the work table, approximately 300mm from the welder arm motion axis.

Annotations

The dataset includes a manifest with the following columns: CATEGORY, WELD_TYPE, THICKNESS_MM, STEEL_TYPE, SAMPLES, CURRENT_A, VOLTAGE_V, GAS_BAR, ROBOT_SPEED_CPM, DIRECTORY, SUBDIRS, and SPLIT.

The CATEGORY column describes the welding defect, one of 12 categories.

  • Good
  • Excessive_Convexity
  • Undercut
  • Lack_of_Fusion
  • Porosity
  • Spatter
  • Burnthrough
  • Porosity_w_Excessive_Penetration
  • Excessive Penetration
  • Crater_Cracks
  • Warping
  • Overlap

Limitations

The dataset may exhibit some label noise since the annotations were made without post-weld validation by a welding expert, and the labels represent the intended defect type, although a single weld could contain multiple defects. Additionally, while sensor recordings were triggered simultaneously using a script, the inherent differences in device response times may result in slight misalignments within the multimodal data.

Personal and Sensitive Information

This dataset does not contain personal identifiable information.

Uses

This dataset is intended to enable multimodal defect detection research and should not be used for commercial purposes.

License 

Intel Research Use License Agreement

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