Enhanced structural damage detection using computer vision and stochastic subspace analysis within a Bayesian framework

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The methodology improves accuracy in detecting structural damage, facilitating enhanced safety management.
Validation on a numerical truss model showed superior performance in damage severity prediction compared to existing techniques.
The approach uses principal component analysis to determine optimal system order from displacement responses, enhancing data accuracy.
Real-time structural health monitoring is supported through effective damage location across various severity levels.

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This novel approach employs computer vision and Bayesian methods to enhance damage localization in structures, highlighting safety improvements.

Banerjee et al. (2025) studied this question.

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This novel approach employs computer vision and Bayesian methods to enhance damage localization in structures, highlighting safety improvements.