4.7 Article

A novel rotated sigmoid weight function for higher performance in heterogeneous deformation measurement with digital image correlation

期刊

OPTICS AND LASERS IN ENGINEERING
卷 159, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.optlaseng.2022.107214

关键词

Digital image correlation; Heterogeneous deformation measurement; Self-adaptive algorithm

类别

资金

  1. National ST Major Project [ZX069]
  2. National Natural Science Foundation of China [51705279]
  3. Tsinghua University Initiative Scientific Research Program

向作者/读者索取更多资源

This paper proposes a novel rotated sigmoid weight (RSW) function for digital image correlation (DIC), and the experiment results show that DIC combined with RSW function (RSW-DIC) achieves the best spatial resolution without sacrificing much measurement resolution.
Conventional digital image correlation (C-DIC) combined with a rotated Gaussian weight (RGW) function for subset has demonstrated attractive ability in resolving heterogeneous deformation parameters. To further improve the performance, the selection of an optimum weight function becomes the key issue. In this paper, a novel rotated sigmoid weight (RSW) function is proposed. RSW function aims to get a more uniform weight distribution near the subset center, and to realize the continuous change of the equivalent subset size as well. The performance of the RSW function is compared with the Gaussian weight (GW) function, RGW function, the rotated inverse distance weight (RIDW) function and the inverse distance square weight (RIDSW) function through Star 5 image set from the DIC challenge 2.0 and the simulated image set. A total of six methods with different weight functions and rotated weights are systematically compared. The experiment results clearly show that DIC combined with RSW function (i.e. RSW-DIC) has the best spatial resolution without sacrificing much measurement resolution. The spatial resolution of RSW-DIC is only about half of the other methods for both first- and second-order shape functions when a big initial subset size is adopted.

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