SUN Bin, WU Yanming, YE Jun, YI Wu, ZHU Hongyan, FAN Shanshan, CHEN Jialiang. Low-code Visualization AI Technology Accelerating the Intelligentization of Ship Welding Process[J]. Development and Application of Materials, 2023, 38(5): 58-69.
Citation: SUN Bin, WU Yanming, YE Jun, YI Wu, ZHU Hongyan, FAN Shanshan, CHEN Jialiang. Low-code Visualization AI Technology Accelerating the Intelligentization of Ship Welding Process[J]. Development and Application of Materials, 2023, 38(5): 58-69.

Low-code Visualization AI Technology Accelerating the Intelligentization of Ship Welding Process

  • The intelligent application research and innovation in welding quality analysis and evaluation requires industrial mechanism models and analytical methods for visualization, low-code development, and intelligent construction. The low-code visualization analysis of the welding process provides a signal analysis method based on mechanism models, which can help the shipbuilding industry solve quality problems during the welding process. This software includes analysis functions such as U-I phase diagrams, feature analysis, and short-circuit-specific analysis. Using ship engine welding as a case study, users can independently build a welding quality rating model according to the U-I phase diagrams and other functions, and achieve real-time output of on-line welding quality rating. This verifies the effectiveness of the software in welding quality analysis and evaluation, which can improve the efficiency and accuracy of the welding quality evaluation.
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