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As an machining tool in the field of high-end equipment trans-mission, the precision and performance of the gear grinding machine have a decisive effect on the quality and efficiency of the final product. Establishing an accurate error model and identifying the key error terms are crucial for enhancing the machining accuracy of the gear grinding machine. This study explores the spatial error modeling of gear grinding machines using the kinematics theory of multi-body systems. By applying this theory, the research analyzes the kinematics of gear grinding machines, delves into the machine tool structure and geometric errors, and develops a machining accuracy model that incorporates 30 geometric errors. Based on this model, the Sobol global sensitivity analysis method and an improved Monte Carlo algorithm are employed to meticulously calculate the sensitivity coefficients of geometric errors’ impact on machining accuracy. This approach clarifies how each geometric error affects machine tool performance and offers a vital theoretical foundation for the design, manufacturing, optimization, and error compensation of gear grinding machines.

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Modeling of Machining Accuracy and Sensitivity Analysis of Spatial Error in Worm Wheel Gear Grinding Machines

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Zhifeng Liu,
  • Xuezheng Teng,
  • Baobao Qi,
  • Li Liu,
  • Xian Liu

摘要

As an machining tool in the field of high-end equipment trans-mission, the precision and performance of the gear grinding machine have a decisive effect on the quality and efficiency of the final product. Establishing an accurate error model and identifying the key error terms are crucial for enhancing the machining accuracy of the gear grinding machine. This study explores the spatial error modeling of gear grinding machines using the kinematics theory of multi-body systems. By applying this theory, the research analyzes the kinematics of gear grinding machines, delves into the machine tool structure and geometric errors, and develops a machining accuracy model that incorporates 30 geometric errors. Based on this model, the Sobol global sensitivity analysis method and an improved Monte Carlo algorithm are employed to meticulously calculate the sensitivity coefficients of geometric errors’ impact on machining accuracy. This approach clarifies how each geometric error affects machine tool performance and offers a vital theoretical foundation for the design, manufacturing, optimization, and error compensation of gear grinding machines.