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<p>Position-independent geometric errors (PIGEs) of rotary axes are critical factors compromising the volumetric accuracy of five-axis machine tools. However, existing identification methods utilizing Double Ball Bars (DBB) often struggle to balance measurement efficiency with identification accuracy, primarily due to the coupling effects of instrument setup errors. To address this challenge, this paper proposes a streamlined identification methodology capable of resolving eight PIGEs using only three DBB installation setups. A comprehensive mathematical model is established based on homogeneous coordinate transformations, which explicitly incorporates both the rotary axis PIGEs and the DBB setup errors. Crucially, a practical measurement procedure is introduced to quantify and decouple the setup errors prior to identification, thereby preventing them from confounding the PIGE results. Experimental validation demonstrates the robustness of the proposed method: post-compensation, the maximum absolute geometric deviation was significantly reduced from <InlineEquation ID="IEq1"><EquationSource Format="TEX">\(103.9~\upmu \text{ m}\)</EquationSource></InlineEquation> to a residual value of <InlineEquation ID="IEq2"><EquationSource Format="TEX">\(0.46~\upmu \text{ m}\)</EquationSource></InlineEquation>, and the average PIGE magnitude was reduced to a sub-micron level. These results confirm that the proposed method achieves high-precision error compensation with significantly reduced procedural complexity, making it highly suitable for industrial applications requiring efficient machine calibration.</p>

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A streamlined identification method for position-independent geometric errors of rotary axes in five-axis machine tools considering setup errors

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月31日

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  • Yulin Wang,
  • Xiang Li,
  • Huanlao Liu,
  • Xuachuan Mei

摘要

Position-independent geometric errors (PIGEs) of rotary axes are critical factors compromising the volumetric accuracy of five-axis machine tools. However, existing identification methods utilizing Double Ball Bars (DBB) often struggle to balance measurement efficiency with identification accuracy, primarily due to the coupling effects of instrument setup errors. To address this challenge, this paper proposes a streamlined identification methodology capable of resolving eight PIGEs using only three DBB installation setups. A comprehensive mathematical model is established based on homogeneous coordinate transformations, which explicitly incorporates both the rotary axis PIGEs and the DBB setup errors. Crucially, a practical measurement procedure is introduced to quantify and decouple the setup errors prior to identification, thereby preventing them from confounding the PIGE results. Experimental validation demonstrates the robustness of the proposed method: post-compensation, the maximum absolute geometric deviation was significantly reduced from \(103.9~\upmu \text{ m}\) to a residual value of \(0.46~\upmu \text{ m}\), and the average PIGE magnitude was reduced to a sub-micron level. These results confirm that the proposed method achieves high-precision error compensation with significantly reduced procedural complexity, making it highly suitable for industrial applications requiring efficient machine calibration.