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Purpose <p>This research introduce a short time-enhanced frequency domain decomposition (ST-EFDD) method for accurate identification of modal parameters, including eigenfrequencies and damping ratios, in mass time-varying structures.</p> Methods <p>The method integrates segmented processing with frequency-domain analysis to enhance local vibration characterization, improves computational efficiency via adaptive window sizing, and is validated on both a simply supported beam and a corn combine harvester under mass time-varying conditions.</p> Results <p>The results reveal a clear decay trend in the eigenfrequencies of the corn combine harvester, with defined variation ranges across 12 identified modes. Statistical analysis of the damping ratios extracted via ST-EFDD shows minimal temporal fluctuation across modal orders.</p> Conclusion <p>The modal characteristics of the mass time-varying beam were identified using both ST-SSI and ST-EFDD methods. Comparative results indicate that ST-EFDD offers superior performance under conditions with limited excitation sources. Accordingly, ST-EFDD is applied to the corn combine harvester system to extract modal parameters during field operation, where the structure is subject to complex excitations.</p>

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Identification of Modal Parameters Using the ST-EFDD Method for a Time-Varying Mass System in a Corn Combine Harvester

  • 期刊论文

  • 发表日期：

    2025年7月31日

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  • Liang Li,
  • Xiaoke Li,
  • Yanchun Yao,
  • Xibin Li,
  • Jida Wu,
  • Duanyang Geng

摘要

Purpose

This research introduce a short time-enhanced frequency domain decomposition (ST-EFDD) method for accurate identification of modal parameters, including eigenfrequencies and damping ratios, in mass time-varying structures.

Methods

The method integrates segmented processing with frequency-domain analysis to enhance local vibration characterization, improves computational efficiency via adaptive window sizing, and is validated on both a simply supported beam and a corn combine harvester under mass time-varying conditions.

Results

The results reveal a clear decay trend in the eigenfrequencies of the corn combine harvester, with defined variation ranges across 12 identified modes. Statistical analysis of the damping ratios extracted via ST-EFDD shows minimal temporal fluctuation across modal orders.

Conclusion

The modal characteristics of the mass time-varying beam were identified using both ST-SSI and ST-EFDD methods. Comparative results indicate that ST-EFDD offers superior performance under conditions with limited excitation sources. Accordingly, ST-EFDD is applied to the corn combine harvester system to extract modal parameters during field operation, where the structure is subject to complex excitations.