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This review aims to summarize the advancements in signal processing methods for the structural health monitoring of bridges.

Signal processing methods for structural health monitoring of bridges: a comprehensive review of classical, data-driven, and hybrid approaches

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This review aims to summarize the advancements in signal processing methods for the structural health monitoring of bridges.
Conducted a bibliometric analysis identifying 201 relevant studies on bridge health monitoring.
Categorized studies into traditional, data-driven, and hybrid methodologies.
Performed a keyword co-occurrence analysis to identify trends in monitoring technologies.
Identified traditional methods as foundational for modal and condition assessment of bridges.
Highlighted the increasing use of machine learning to address complex structural behavior and environmental variability.
Noted ongoing challenges such as poor interpretability of models and lack of standardized datasets.

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Comprehensive review categorizes signal processing methods in bridge health monitoring, highlighting advances and challenges.

Hajivand et al. (2026) studied this question.

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