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This is a Observational study (also classified as: In Vitro Study).

August 25, 2025Open Access

Research on Monitoring and Intelligent Identification of Typical Defects in Small and Medium-Sized Bridges Based on Ultra-Weak FBG Sensing Array

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Research demonstrates effective monitoring and damage recognition in bridges, suggesting machine learning improves detection accuracy.

The method enhances damage recognition accuracy and efficiency in bridge monitoring, allowing for better infrastructure maintenance.
Key findings show that the integration of machine learning with strain data improves damage classification capabilities significantly.
This approach utilizes an ultra-weak fiber Bragg grating sensing array to monitor multi-point strain data in bridges.
While promising, this technique highlights the need for improved detection of atypical damages beyond visual maps.

Lin et al. (2025) studied this question.

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