Descriptor: Intelligent Laser Welding State Detection Continuous Frame Image Dataset (MoltenPool2D)

The study aims to construct a high-quality continuous frame image dataset of laser welding to support the research of automatic welding state detection in intelligent laser welding. The dataset is collected by our self-built welding platform and a high-resolution industrial camera. The dataset not only makes up for the shortage of existing laser welding video data, but also provides rich molten pool and welding process context information, which facilitates the development and verification of condition detection algorithms. The article first introduces the collection method of the dataset, and then analyzes the quality of the dataset, including the distribution law of various parameters of the data, the statistical analysis of the molten pool characteristics, etc. In order to verify the effectiveness of the dataset in tasks such as welding state recognition, corresponding experiments are designed and the record and storage method of the dataset are introduced. The public release of the MoltenPool2D dataset will provide an important resource for intelligent welding research and promote the development of intelligent welding technology. In the future, we will continue to update and expand the dataset to further enhance its scientific research value and application potential. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>IEEE SOCIETY/COUNCIL</b> Industrial Electronics Society <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>DATA TYPE/LOCATION</b> Movie/Video; Shanghai, China <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>DATA DOI/PID</b> 10.21227/qj7e-bw83

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Publication Details

Journal
IEEE data descriptions.
Published
2025-01-01
DOI
https://doi.org/10.1109/ieeedata.2025.3596865
Primary Topic
Welding Techniques and Residual Stresses
Type
article
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article

Descriptor: Intelligent Laser Welding State Detection Continuous Frame Image Dataset (MoltenPool2D)

Jiuchao Qian, Qi Hu, Zhuguo Li, Songlin Li et al.
IEEE data descriptions.
Welding Techniques and Residual Stresses
article

Descriptor: Intelligent Laser Welding State Detection Continuous Frame Image Dataset (MoltenPool2D)

Jiuchao Qian, Qi Hu, Zhuguo Li, Songlin Li, Haonan Zhang, Jiawei Fan
article en

Abstract

The study aims to construct a high-quality continuous frame image dataset of laser welding to support the research of automatic welding state detection in intelligent laser welding. The dataset is collected by our self-built welding platform and a high-resolution industrial camera. The dataset not only makes up for the shortage of existing laser welding video data, but also provides rich molten pool and welding process context information, which facilitates the development and verification of condition detection algorithms. The article first introduces the collection method of the dataset, and then analyzes the quality of the dataset, including the distribution law of various parameters of the data, the statistical analysis of the molten pool characteristics, etc. In order to verify the effectiveness of the dataset in tasks such as welding state recognition, corresponding experiments are designed and the record and storage method of the dataset are introduced. The public release of the MoltenPool2D dataset will provide an important resource for intelligent welding research and promote the development of intelligent welding technology. In the future, we will continue to update and expand the dataset to further enhance its scientific research value and application potential. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>IEEE SOCIETY/COUNCIL</b> Industrial Electronics Society <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>DATA TYPE/LOCATION</b> Movie/Video; Shanghai, China <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>DATA DOI/PID</b> 10.21227/qj7e-bw83

IEEE data descriptions.Vol. 2
Shanghai Jiao Tong University (CN)
Affordable and clean energy
Openalex Percentile: Top 80%
Welding Techniques and Residual Stresses
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