Noise reduction for DIC measurements

Abstract

Digital image correlation (DIC) is well known as a contact‐less, full‐field strain and displacement measuring method. The use of the method is widely spread in experimental mechanics. Nevertheless, there are error sources such as light settings, speckle pattern and noisy images, which strongly affect measurement quality, but often stays uninvestigated. Therefore, this work outlines a simple routine to identify errors and enhance the accuracy of DIC measurements. A calibration sample adapted to the specifications of the setup using the beam theory to link machine displacement, DIC measurements and forces. All evaluations are done in the commercial software ISTRA4D. The noise in the measurements is reduced to an error of under two per cent. The routine allows estimating the quality of the images before performing the experiments. Furthermore, the routine is transferable to all experimental setups. The calibration of the setup allows getting reliable experimental results with a known error. With this estimated stochastic error, the advantages of DIC can be used to evaluate mechanical experiments such as three‐point bending tests on single struts of an open cell metal foam.