Measurement of Whole-Field Surface Displacements and Strain Using a Genetic Algorithm Based Intelligent Image Correlation Method

Abstract

This paper presents an intelligent digital image correlation technique that uses genetic algorithms to measure surface displacements and strains. Speckle patterns are spray painted on the surface of interest and pictures taken before and during loading. Subpixel resolution, required for measuring displacements and strains accurately, is obtained by using interpolation methods. An innovative procedure based on genetic algorithms (GA) is used that has the potential to give the two displacements and four deformation gradients directly for a subset being investigated. This paper presents the algorithm for the six variables, but uses only the displacements (two variables) to calculate the 2-D strain fields. The genetic algorithms can guarantee a solution based on a comprehensive calibration procedure. The focus of this paper is the description of the GA routine used for the search process as well as the calibration scheme. Measurement results are presented for rigid-body displacement, 1-D and 2-D strain as proof of concept. Some potential applications for this work are to extract surface displacements and strains on the surfaces of aircraft, spacecraft and reusable launch vehicles, submarine and ship hulls, civil infrastructures such as bridges, dams and buildings, and biomedical imaging applications.