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Development of in-process welding torch position control system using AI technology

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Abstract

The authors have developed a torch position control system for narrow groove automatic TIG welding. This system can detect the feature point (electrode, wire, groove wall, and weld pool) positions in a weld pool image, calculate the relative positions, and move the electrode and wire to the correct positions. In order to identify the wavelength range that is less susceptible to arc light when capturing weld pool images, spectroscopic analysis was performed and a 1000-nm bandpass filter was selected. Since the brightness distribution suitable for detection differs for each feature point, weld pool images were captured with multiple exposure times. In order to accurately detect the feature points of various weld pool images, AI technology (the pose estimation model DarkPose) that can improve detection accuracy by adding training data was used. When the detection models were evaluated, it was found that the electrode, wire, and groove wall were detected with high accuracy. The torch position control system using the developed feature point detection technology was implemented. The system accurately detected the feature point positions and moved the electrode and wire to the correct position when the feature point position was misaligned. Also, the processing speed of the system was sufficient for torch position control of actual automatic TIG welding.

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Data Availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors appreciate Tetsuo Sakai, Yasutomo Shiomi, and Taisuke Washitani of Toshiba Corporation, and Naoto Seto, Masahiro Horie, and Yoshiaki Yamasaki of Toshiba Infrastructure Systems & Solutions Corporation for their cooperation in the development of the feature point detection technology, and Yusuke Maruyama and Ryohei Tozaki of Toshiba IT & Control Systems Corporation for their help in constructing the welding torch position control system.

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Authors and Affiliations

  1. Welding Technology Group, Power Systems Production Control Department, Power System Division, Toshiba Energy Systems & Solutions Corporation, 2-4, Suehiro-Cho, Tsurumi-Ku, Yokohama, 230-0045, Japan

    S. Amano, Y. Tsujimura & T. Ogawa

  2. Media AI Laboratory, Advanced Intelligent Systems Laboratories, Corporate Research & Development Center, Toshiba Corporation, 1, Komukaitoshiba-Cho, Saiwai-Ku, Kawasaki, 212-8582, Japan

    T. Shibata

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  1. S. Amano
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  2. Y. Tsujimura
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  3. T. Ogawa
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Correspondence to S. Amano.

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Amano, S., Tsujimura, Y., Ogawa, T. et al. Development of in-process welding torch position control system using AI technology. Weld World 67, 1223–1234 (2023). https://doi.org/10.1007/s40194-023-01486-7

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  • DOI: https://doi.org/10.1007/s40194-023-01486-7

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