Adaptive matching strategies for 3D digital image correlation in strain measurement of an aerostat envelope

To address the limitations of two-dimensional digital image correlation (2D-DIG) in measuring strain on the aerostat envelope, the more precise 3D-DIG has been introduced to handle curved surfaces. However, the increased computational load of 3D-DIG requires more efficient correlation strategies. This paper evaluates three basic matching strategies and introduces two adaptive strategies to enhance the efficiency of 3D-DIG. The experimental results show that the adaptive composite matching (AGM) strategy automatically switches strategies based on deformation, improving the matching correlation. Meanwhile, the adaptive grouping matching (AGM) strategy dynamically adjusts image groups based on real-time data, optimizing the computational speed and enhancing measurement flexibility. These strategies provide crucial support for the application of 3D-DIG in the monitoring aerostat envelope strain, especially in managing significant or uneven deformations. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.