GA-based laser speckle pattern digital image correlation method for surface strain measurements

Abstract

This article introduces an innovative technique that integrates a genetic algorithm (GA)-based digital image correlation with laser speckle photography for the estimation of surface displacements in structures. The images (before and after deformation) are digitized using a digital camera, and the grayscale intensity matrices are read and processed by an image processing algorithm. The two matrices of the images are then inputted into GA-based optimizer that utilizes an advanced cross-correlation fitness function to approximate the surface displacements. Furthermore, the surface strains are computed from the displacements using radial basis function differentiation and interpolation. The computed displacements are compared with simulated results obtained by the boundary element method. Close agreement between the two results proves the validity of the developed noncontact technique for accurately estimating surface displacements and strains. These experimentally estimated displacements can further be used in an inverse technique to detect and characterize subsurface cavities in structures.