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<p>In response to the demand for high-precision in-situ repair of cracks on hydro turbine runner blades, this study proposes an integrated optimization framework that integrates robotic milling position-posture planning with process parameter control. The method aims to improve both geometric accuracy and surface quality during robotic milling of complex curved surfaces. Firstly, a digital modeling process is employed to characterize the crack regions and generate machining trajectories. To ensure smooth and stable execution of tool paths, a novel position-posture smoothing algorithm based on spline fitting and bilateral weighting is introduced. This effectively mitigates abrupt posture changes, reduces cutting force fluctuations, and enhances the kinematic stability of the robotic system. Secondly, key process parameters including feed rate and depth of cut are jointly optimized in combination with the smoothed tool posture, aiming to suppress chatter, improve dynamic stability, and enhance surface integrity. Experimental validation is conducted using machining error and surface roughness as evaluation indicators. Results show that the maximum surface deviation is reduced to 0.303&#xa0;mm, and surface roughness Ra values are controlled below 3&#xa0;μm, indicating a substantial improvement in machining consistency and quality. The proposed dual-level optimization strategy demonstrates strong potential in ensuring high-accuracy and high-efficiency robotic milling for complex blade repairs. It provides a solid theoretical foundation and practical methodology for intelligent and automated maintenance in large-scale hydropower applications, and paves the way for future integration with adaptive sensing and digital twin technologies.</p>

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Integrated optimization of posture planning and process parameters of in-situ robotic milling for cracks repair on hydro turbine runner

  • 期刊论文

  • 发表日期：

    2026年3月11日

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  • Hui Liu,
  • Shengqiang Zhao,
  • Jia Zhao,
  • Lin Zhou,
  • Cencen Yang,
  • Yi Zhang,
  • Xiaowei Tang,
  • Jiahao Zhang,
  • Jingnan Yan

摘要

In response to the demand for high-precision in-situ repair of cracks on hydro turbine runner blades, this study proposes an integrated optimization framework that integrates robotic milling position-posture planning with process parameter control. The method aims to improve both geometric accuracy and surface quality during robotic milling of complex curved surfaces. Firstly, a digital modeling process is employed to characterize the crack regions and generate machining trajectories. To ensure smooth and stable execution of tool paths, a novel position-posture smoothing algorithm based on spline fitting and bilateral weighting is introduced. This effectively mitigates abrupt posture changes, reduces cutting force fluctuations, and enhances the kinematic stability of the robotic system. Secondly, key process parameters including feed rate and depth of cut are jointly optimized in combination with the smoothed tool posture, aiming to suppress chatter, improve dynamic stability, and enhance surface integrity. Experimental validation is conducted using machining error and surface roughness as evaluation indicators. Results show that the maximum surface deviation is reduced to 0.303 mm, and surface roughness Ra values are controlled below 3 μm, indicating a substantial improvement in machining consistency and quality. The proposed dual-level optimization strategy demonstrates strong potential in ensuring high-accuracy and high-efficiency robotic milling for complex blade repairs. It provides a solid theoretical foundation and practical methodology for intelligent and automated maintenance in large-scale hydropower applications, and paves the way for future integration with adaptive sensing and digital twin technologies.