Image-Based Hidden Damage Detection Method: Combining Stereo Digital Image Correlation and Finite Element Model Updating.

Maintenance and damage detection of structures are crucial for ensuring their safe usage and longevity. However, damage hidden beneath the surface can easily go unnoticed during inspection and assessment processes. This study proposes a detection method based on image techniques to detect and assess internal structural damage, breaking the limitation of traditional image methods that only analyze the structure's surface. The proposed method combines full-field response on the structure's surface with finite element model updating to reconstruct the structural model, using the reconstructed model to detect and assess hidden structural damage. Initially, numerical experiments are conducted to generate known damaged areas and parameter distributions. Data from these experiments are used to update the finite element model, establish and validate the proposed model updating method, and assess its accuracy in evaluating hidden damage, achieving an accuracy rate of 90%. Furthermore, discussions on more complex damage scenarios are carried out through numerical experiments to demonstrate the feasibility and applicability of the proposed method in reconstructing different forms of damage. Ultimately, this study utilizes stereoscopic digital imaging techniques to acquire full-field information on surfaces, and applies the proposed method to reconstruct the structure, enabling the detection and assessment of hidden damage with an accuracy rate of 86%.