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<p>Robotic belt grinding has become an indispensable precision machining technique for aero-engine blade manufacturing, valued for its exceptional flexibility, efficiency, and accuracy. While offering these advantages, the process generates significant heat accumulation in the cutting zone, leading to potentially detrimental workpiece temperature elevation. This study presents an innovative multi-scale modeling approach that decomposes the complex grinding process into three integrated components: a macroscopic finite element model for tool-workpiece interaction, a microscopic mechanical-thermal coupled model for cutting zone temperature analysis, and a macroscopic workpiece temperature field model. By leveraging the fundamental coupling relationship between grinding force and heat generation at the microscale, our approach efficiently predicts both surface and subsurface temperature distributions across various processing parameters while maintaining computational efficiency. Experimental validation through robotic belt grinding tests demonstrates strong agreement with simulation results, achieving an average prediction error of just 3.16%. The developed model establishes a robust theoretical framework for accurate temperature field prediction in industrial grinding applications.</p>

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Finite element method and experimental research on the temperature field of GH4169 in robotic belt grinding

  • 期刊论文

  • 发表日期：

    2025年6月10日

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  • Xinpeng Zu,
  • Yifei Wang,
  • Yadong Gong,
  • Mingjun Liu,
  • Zeming Li,
  • Yao Sun,
  • Jibin Zhao

摘要

Robotic belt grinding has become an indispensable precision machining technique for aero-engine blade manufacturing, valued for its exceptional flexibility, efficiency, and accuracy. While offering these advantages, the process generates significant heat accumulation in the cutting zone, leading to potentially detrimental workpiece temperature elevation. This study presents an innovative multi-scale modeling approach that decomposes the complex grinding process into three integrated components: a macroscopic finite element model for tool-workpiece interaction, a microscopic mechanical-thermal coupled model for cutting zone temperature analysis, and a macroscopic workpiece temperature field model. By leveraging the fundamental coupling relationship between grinding force and heat generation at the microscale, our approach efficiently predicts both surface and subsurface temperature distributions across various processing parameters while maintaining computational efficiency. Experimental validation through robotic belt grinding tests demonstrates strong agreement with simulation results, achieving an average prediction error of just 3.16%. The developed model establishes a robust theoretical framework for accurate temperature field prediction in industrial grinding applications.