Bridge operational modal analysis method based on fusion of structural dynamics and gaussian process

By combining bridge structural dynamics with a Gaussian process model and eliminating the influence of external excitations, the problem of parameter offset in bridge operation modal analysis was solved, thereby improving the accuracy and reliability of bridge health monitoring and supporting the full life cycle management of the structure.

CN121479911BActive Publication Date: 2026-03-31ANHUI TRANSPORTATION HLDG GRP CO LTD
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Patent Information

Application Number
CN202610013249.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-01-07
Publication Date
2026-03-31
Estimated Expiration
2046-01-07

AI Technical Summary

Technical Problem

The modal parameter identification shift in bridge operation modal analysis methods under changes in external excitation leads to reduced accuracy and reliability of health monitoring, making it difficult to effectively distinguish between external excitation effects and structural damage.

Method used

By combining the bridge structural dynamics model with the Gaussian process model, and eliminating the influence of external excitation through modal force power spectral density and the Gaussian process model, the bridge modal parameters are identified through iterative updates using the expectation-maximization algorithm and variational inference technique.

Benefits of technology

It improves the accuracy and reliability of bridge structural health assessment, reduces false alarm rate, stably identifies key modal parameters, and supports full life cycle management of structures.

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Abstract

The application discloses a bridge operation modal analysis method based on structural dynamics and Gaussian process fusion, and can be used for bridge structure health monitoring. Acceleration sensors are arranged at key positions of the bridge to collect vibration responses in an operation state; mode force power spectral densities of each mode are extracted through frequency domain analysis as external excitation strength indexes. The indexes are taken as Gaussian process inputs and hidden variables are introduced to quantize influences of excitation changes on natural frequencies, damping ratios and vibration modes; an expectation-maximization algorithm is used to iteratively identify structural dynamics parameters and Gaussian process hyperparameters. Finally, the bridge modal parameters after excitation disturbances such as wind and vehicle flow are removed and the hyperparameters representing working conditions are obtained, and long-term tracking, evaluation and prediction of the bridge structure health are realized.
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