A Nonlocal Strain Measure for Digital Image Correlation

TL;DR

This paper introduces a robust nonlocal strain measure for digital image correlation that effectively handles noisy and irregular displacement fields, providing accurate and noise-resistant strain analysis especially in regions with steep gradients.

Contribution

The paper presents a novel nonlocal strain measure that is robust to noise and irregularities, aligning with classical strain for smooth fields and improving analysis in steep gradient regions.

Findings

The nonlocal strain measure remains well-defined under noise and irregularities.

It provides a high signal-to-noise ratio by filtering high-frequency content.

Numerical examples demonstrate its effectiveness in steep gradient problems.

Abstract

We propose a nonlocal strain measure for use with digital image correlation (DIC). Whereas the traditional notion of compatibility (strain as the derivative of the displacement field) is problematic when the displacement field varies substantially either because of measurement noise or material irregularity, the proposed measure remains robust, well-defined and invariant under rigid body motion. Moreover, when the displacement field is smooth, the classical and nonlocal strain are in agreement. We demonstrate, via several numerical examples, the potential of this new strain measure for problems with steep gradients. We also show how the nonlocal strain provides an intrinsic mechanism for filtering high frequency content from the strain profile and so has a high signal to noise ratio. This is a convenient feature considering image noise and its impact on strain calculations.