基于坡口形态视觉感知的焊接参数自主优化研究

Research on autonomous optimization of welding parameters based on visual perception of groove shape

  • 摘要: 为应对机器人焊接智能化升级的挑战,本研究创新性地提出一种基于坡口形态视觉感知的焊接参数自主优化策略,重点增强焊接系统对大尺寸坡口的动态适应能力。通过构建几何约束驱动的摆动模型,并集成激光视觉传感器实现坡口形貌的实时捕捉,系统能够依据坡口特征动态调整摆动轨迹。研究采用对比实验与轮廓精度分析双重验证方法,结果表明:该摆动模型有效降低了焊缝热密度,同时将焊缝宽度精准控制在11.0-12.1mm区间,显著提升了焊接工艺的稳定性和成形质量。

     

    Abstract: To address the challenge of intelligent upgrading of robotic welding, this study innovatively proposes an autonomous optimization strategy for welding parameters based on visual perception of groove morphology, focusing on enhancing the dynamic adaptability of the welding system to large-scale grooves. By constructing a geometric constraint-driven swing model and integrating a laser vision sensor to achieve real-time capture of groove topography, the system can dynamically adjust the swing trajectory based on groove characteristics. The study used a dual verification method of comparative experiments and contour accuracy analysis, and the results showed that the swing model effectively reduced the heat density of the weld, while accurately controlling the weld width within the range of 11.0-12.1 mm, significantly improving the stability and forming quality of the welding process.

     

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