Automated AI-DIC marker-less technique for tracking displacements of large structures

Abstract

Markers are crucial for measuring the displacement of large structures using digital image correlation (DIC). In general, creating or affixing artificial markers on large structures is cha llenging. Several studies in the past have addressed this challenge by employing marker-less or target-free approaches. In this work, we integrate an AIbased non-intersecting poly-shape marker identification technique with the DIC program that uses the structural pattern as a marker and automates the selection of the region of interest by enabling strong correlation criteria to obtain the displacements in real-time. The proposed AI-DIC algorithm segments non-intersecting poly-shape markers from the images of the target structure based on the features detected by the KAZE feature detector and descriptors. Further, the investigated marker or the natural structural pattern is automatically given as an input region of interest to the DIC program. Moreover, it considers the marker as a template, correlates it with all subsequent images, and analyzes the displacements and frequencies of the target structure. In addition, the AI-DIC algorithm is realized on an in-house cantilever beam experiment where the images are acquired and processed in real-time.