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Purpose <p>To address the limitations of existing modal contribution analysis methods requiring full-structure measurements during machining processes, this study proposes a novel time-domain approach for online identification of principal vibration modes under variable operating conditions.</p> Methods <p>A Kalman filtering-based time-domain methodology is developed that only requires single-point vibration measurements. The method enables real-time tracking of modal participation ratios during cutting operations with varying parameters and spindle positions. Comparative simulations validate the approach against conventional operational deformation shape analysis, followed by experimental verification through cutting vibration tests.</p> Results <p>Experimental results demonstrate the method's effectiveness in identifying modal contributions across changing spindle speeds. Key findings reveal: (1) Progressive transition of dominant vibration modes from lower to higher orders with speed increases, (2) Corresponding energy migration from low-frequency to high-frequency vibration components, (3) Successful implementation under variable cutting conditions without requiring full-structure instrumentation.</p> Conclusions <p>The proposed Kalman filtering technique provides a practical solution for online modal analysis in CNC machining, overcoming traditional measurement constraints. The identified speed-dependent modal transition patterns offer new insights for vibration suppression strategies and machine tool optimization, particularly in high-speed machining applications where dynamic characteristics vary significantly with operational parameters.</p>

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A Method for Vibration Analysis of Machine Tools Under Variable Cutting Excitation Based on Modal Participation Ratio

  • 期刊论文

  • 发表日期：

    2025年4月23日

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  • Guirong Han,
  • Yili Peng,
  • Xubing Chen,
  • Yu Qian,
  • Yongkang Jiao

摘要

Purpose

To address the limitations of existing modal contribution analysis methods requiring full-structure measurements during machining processes, this study proposes a novel time-domain approach for online identification of principal vibration modes under variable operating conditions.

Methods

A Kalman filtering-based time-domain methodology is developed that only requires single-point vibration measurements. The method enables real-time tracking of modal participation ratios during cutting operations with varying parameters and spindle positions. Comparative simulations validate the approach against conventional operational deformation shape analysis, followed by experimental verification through cutting vibration tests.

Results

Experimental results demonstrate the method's effectiveness in identifying modal contributions across changing spindle speeds. Key findings reveal: (1) Progressive transition of dominant vibration modes from lower to higher orders with speed increases, (2) Corresponding energy migration from low-frequency to high-frequency vibration components, (3) Successful implementation under variable cutting conditions without requiring full-structure instrumentation.

Conclusions

The proposed Kalman filtering technique provides a practical solution for online modal analysis in CNC machining, overcoming traditional measurement constraints. The identified speed-dependent modal transition patterns offer new insights for vibration suppression strategies and machine tool optimization, particularly in high-speed machining applications where dynamic characteristics vary significantly with operational parameters.