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A decentralized difference-based improved method for compensating undermatched systematic error in digital image correlation
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DOI：10.1016/j.optlaseng.2026.110046.png)
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Abstract
En 中文
In digital image correlation (DIC) measurements of non-uniform deformation fields, the undermatched problem is often a key factor limiting measurement accuracy. Existing optimization strategies for undermatched problem mostly rely on a priori assumptions about the order of the deformation field to be measured. This prerequisite imposes significant limitations on their application in unpredictable complex real-world scenarios. To address this issue, a decentralized difference-based improved method for undermatched systematic error is proposed. This method can effectively compensate for undermatched errors in non-uniform deformation fields without requiring any prior information. Numerical simulations results show that the method is suitable for high-order non-uniform deformation fields, can reduce the undermatched error of the first-order shape function by 97.0%. It can achieve higher computational accuracy and stability than mainstream second-order shape function. Its optimization performance has been effectively validated in practical engineering applications.
Keywords:
Non-uniform deformation fields
Digital image correlation
Undermatched systematic error
Shape function
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