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Bayesian method for quantitative damage evaluation of concrete using sparse embedded piezoelectric transducers
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AI
DOI：10.1016/j.measurement.2026.120770.png)
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Abstract
En 中文
Accurate damage localization and quantitative evaluation are of great significance for ensuring the reliability and maintenance of the concrete structures, yet they remain inherently challenging owing to uncertainties from modelling, measurement and heterogeneous nature of concrete material. This study proposes a Bayesian method for concrete damage quantitative evaluation based on sparse embedded piezoelectric transducers. Building on stress-wave propagation principles, a damaged subarea division strategy is first applied to the transducer network, retaining only those sensing paths whose scattered responses display high sensitivity as effective sensing paths, and thereby isolating scattered wave information, as a preprocessing stage for damage localization. For each selected path, two diagnostic damage features, time-of-flight (ToF) and energy-based damage index (EDI), are extracted. The ellipse trajectory localization algorithm combined with ToF data is employed to construct the likelihood function, whereas EDI data, affiliated to a prescribed exponential type damage probability distribution, furnishes the prior information required for Bayesian method. Posterior distributions of damage location and effective wave velocity are then obtained through Markov chain Monte Carlo method. In addition, convex envelopes of the boundary points derived by a small number of ellipse trajectories are ultimately utilized to delineate damage contour, providing a quantitative estimation of its potential spatial extent. Validated studies through the meso-level concrete numerical simulations and experiments confirm the efficacy of the proposed sparse-sensing, probability-driven methodology for quantitative damage evaluation in concrete structures.
Keywords:
Structural health monitoring
Embedded piezoelectric transducer
Bayesian method
Meso-level concrete numerical simulation
Damage quantitative evaluation
Journal
IF:
5.6
Papers:
1.9W
Citations:
5.4W