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Background <p>Digital image correlation (DIC) is a widely adopted non-contact method for precise motion and deformation measurement, valued for its high accuracy. However, standard 2D DIC struggles to track relative displacements in materials with significant rigid rotations or out-of-plane displacement interference, such as in monitoring rotating gears. Additionally, the extensive data generated during in-situ monitoring makes DIC-based image matching impractical.</p> Objective <p>This study proposes a method for rapidly identifying identical images from large datasets. The proposed method can also effectively eliminate the impact of rigid rotation and out-of-plane displacement.</p> Methods <p>This study proposes a dynamic period digital image correlation (DP-DIC) method. The technique utilizes the speeded-up robust features (SURF) algorithm to match and select feature points efficiently, addressing the issue of image decorrelation caused by large-angle rotations. Furthermore, a rigid-body matrix restoration algorithm is incorporated to reduce the effects of rigid rotation and out-of-plane displacement partially.</p> Results <p>Validation tests for measuring the dynamic deformation field of rotating gears provide essential data. This data supports gear design optimization, performance evaluation, and lifetime prediction.</p> Conclusion <p>This study proposes a DP-DIC method based on DIC. Validation tests demonstrate that the DP-DIC method is suitable for long-term monitoring of the contact deformation field in periodically rotating gears.</p>

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Study on the Long-Term Monitoring of Contact Deformation Field of Periodic Rotating Gears Using DIC Combined with SURF Algorithm

  • 期刊论文

  • 发表日期：

    2025年5月15日

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  • X. Hou,
  • D. Zeng,
  • X. Huang,
  • H. Zhang,
  • Z. Liu,
  • X. Huang

摘要

Background

Digital image correlation (DIC) is a widely adopted non-contact method for precise motion and deformation measurement, valued for its high accuracy. However, standard 2D DIC struggles to track relative displacements in materials with significant rigid rotations or out-of-plane displacement interference, such as in monitoring rotating gears. Additionally, the extensive data generated during in-situ monitoring makes DIC-based image matching impractical.

Objective

This study proposes a method for rapidly identifying identical images from large datasets. The proposed method can also effectively eliminate the impact of rigid rotation and out-of-plane displacement.

Methods

This study proposes a dynamic period digital image correlation (DP-DIC) method. The technique utilizes the speeded-up robust features (SURF) algorithm to match and select feature points efficiently, addressing the issue of image decorrelation caused by large-angle rotations. Furthermore, a rigid-body matrix restoration algorithm is incorporated to reduce the effects of rigid rotation and out-of-plane displacement partially.

Results

Validation tests for measuring the dynamic deformation field of rotating gears provide essential data. This data supports gear design optimization, performance evaluation, and lifetime prediction.

Conclusion

This study proposes a DP-DIC method based on DIC. Validation tests demonstrate that the DP-DIC method is suitable for long-term monitoring of the contact deformation field in periodically rotating gears.