Pattern recognition-based strategy applied to continuous intensity evolution for quantifying the stress field in digital photoelasticity

In engineering, accurate evaluation of stress fields is paramount to ensure structural integrity and prevent failure in various applications. Despite advances in techniques such as analytical models and computational simulations, challenges remain due to differences in experimental parameters that limit their real-world applicability. Digital photoelasticity offers promise in stress analysis, particularly through isochromatic fringes, but faces hurdles in quantifying stress information from dynamic color changes. To address this gap, this paper proposes a novel approach based on pattern recognition within a single polariscope configuration. By analyzing color trajectories of pixel positions individually, the approach aims to overcome spatial dependencies and improve the accuracy of stress field evaluation. Potential results include a better understanding of dynamic stress behavior and more accurate identification of stress patterns, contributing to improved engineering designs and structural reliability. This approach uses synthetic and experimental photoelasticity videos of disk and ring under diametric compression.