Assessment of Stress and Strain Distribution at Crack Tip Using Digital Image Correlation

Hammoudi, Zaid S.; Alazawi, Dhia A.; Mohammed, Mohanad Nazhan

doi:10.1088/1757-899x/1076/1/012068

Cited by 2 publications

(1 citation statement)

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“…There are two main steps to implement DIC for displacement extraction: integral pixel and subpixel level matching. A multitude of integral pixel algorithms, such as the coarse-fine search and diamond search, have been proposed [ 6 ], and the performance of these methods has been satisfactorily verified by tests [ 7 ]. Chen et al proposed an adaptive point cloud correction algorithm designed to optimize the point cloud structure after image stitching of a multi-camera and improve the accuracy of surface reconstruction [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Subpixel Matching Using Double-Precision Gradient-Based Method for Digital Image Correlation

Liu

Zhang

et al. 2021

Sensors

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Digital image correlation (DIC) for displacement and strain measurement has flourished in recent years. There are integer pixel and subpixel matching steps to extract displacement from a series of images in the DIC approach, and identification accuracy mainly depends on the latter step. A subpixel displacement matching method, named the double-precision gradient-based algorithm (DPG), is proposed in this study. After, the integer pixel displacement is identified using the coarse-fine search algorithm. In order to improve the accuracy and anti-noise capability in the subpixel extraction step, the traditional gradient-based method is used to analyze the data on the speckle patterns using the computer, and the influence of noise is considered. These two nearest integer pixels in one direction are both utilized as an interpolation center. Then, two subpixel displacements are extracted by the five-point bicubic spline interpolation algorithm using these two interpolation centers. A novel combination coefficient considering contaminated noises is presented to merge these two subpixel displacements to obtain the final identification displacement. Results from a simulated speckle pattern and a painted beam bending test show that the accuracy of the proposed method can be improved by four times that of the traditional gradient-based method that reaches the same high accuracy as the Newton–Raphson method. The accuracy of the proposed method efficiently reaches at 92.67%, higher than the Newton-Raphon method, and it has better anti-noise performance and stability.

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Section: Introductionmentioning

confidence: 99%