Scholarlink

Background <p>In complex deformation measurements, systematic errors caused by undermatched shape functions are the primary source of errors in Digital Image Correlation (DIC). There are two important ones among the current undermatched systematic error mitigation methods, Recovery method and Improved Quasi-Gauss Point (IQGP) method, that have shown effectiveness in mitigating such errors, though each has its own inherent limitations. The Recovery method is derived based on first-order shape function, while the IQGP method is setup under the assumption of the second-order displacement field in subset.</p> Objective <p>This study aims to extend and improve both the Recovery method and IQGP method respectively to address these limitations and enhance their applicability while comparing the performance between themselves and with other current methods.</p> Methods <p>As for the Recovery method, the effectiveness in mitigating undermatched systematic errors for second-order shape functions is deduced and verified, which broadens its applicability. As for the IQGP method, a new method called Zero-Error Point (ZEP) method is proposed based on the similar principles while accepting the third-order displacement assumption which basically leads to better and wider adaptability compared to the IQGP method. Other classic undermatched systematic error mitigation method and deconvolution method are also involved into analysis and discussion here.</p> Results <p>The extended Recovery method can now mitigate the undermatched error of second-order shape functions compare to the original one just for the first-order shape function, and the improved IQGP method based on the third-order displacement field can achieve an accuracy improvement of nearly 0.4 pixels compared to the traditional IQGP according to experiment results.</p> Conclusion <p>These advancements enhance the performance of undermatched systematic errors algorithms of DIC, thus improving the ability of DIC in deformation characterization under inhomogeneous deformation.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Advanced Algorithms of Mitigating Undermatched Systematic Error in DIC

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月4日

查看全文
  • J. Hu,
  • H. Miao,
  • J. Xu,
  • R. Zhang,
  • L. Lai,
  • Y. Deng

摘要

Background

In complex deformation measurements, systematic errors caused by undermatched shape functions are the primary source of errors in Digital Image Correlation (DIC). There are two important ones among the current undermatched systematic error mitigation methods, Recovery method and Improved Quasi-Gauss Point (IQGP) method, that have shown effectiveness in mitigating such errors, though each has its own inherent limitations. The Recovery method is derived based on first-order shape function, while the IQGP method is setup under the assumption of the second-order displacement field in subset.

Objective

This study aims to extend and improve both the Recovery method and IQGP method respectively to address these limitations and enhance their applicability while comparing the performance between themselves and with other current methods.

Methods

As for the Recovery method, the effectiveness in mitigating undermatched systematic errors for second-order shape functions is deduced and verified, which broadens its applicability. As for the IQGP method, a new method called Zero-Error Point (ZEP) method is proposed based on the similar principles while accepting the third-order displacement assumption which basically leads to better and wider adaptability compared to the IQGP method. Other classic undermatched systematic error mitigation method and deconvolution method are also involved into analysis and discussion here.

Results

The extended Recovery method can now mitigate the undermatched error of second-order shape functions compare to the original one just for the first-order shape function, and the improved IQGP method based on the third-order displacement field can achieve an accuracy improvement of nearly 0.4 pixels compared to the traditional IQGP according to experiment results.

Conclusion

These advancements enhance the performance of undermatched systematic errors algorithms of DIC, thus improving the ability of DIC in deformation characterization under inhomogeneous deformation.