Abstract

Digital image correlation (DIC) has been widely accepted as a method for displacement and strain measurement and is applied in a variety of engineering fields. Most DIC algorithms encounter errors in measuring the deformation in conditions that involve rotation since they are designed without considering rotation of the deformed object. In this paper, a robust and automated DIC method capable of determining full-field displacement and strain components with random rotations has been presented. The algorithm starts with the determination of the initial position of the seed point in the integer-pixel domain. An approximate rotational angle between the reference and the deformed subset is estimated using an automated feature matching technology. A two-step Newton–Raphson algorithm has been developed for optimizing a suite of variables including displacement, strain and the rotational angle to achieve subpixel accuracy. A reliable propagation scheme, which enables rapid determination of the initial guess for full-field analysis is also proposed. Results from numerical simulations are used to validate the feasibility of the proposed DIC method. An application to 3-point bending with large deflection shows that the algorithm can be employed to measure displacement or strain parameters of the deformed object with arbitrary angles of rotation.

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