Beam bridge structure damage diagnosis method based on line-surface information fusion

By using a line-surface information fusion method and employing locally encrypted fiber optic sensors and sparse optimization techniques, a damage feature matrix is ​​constructed, which solves the problems of high cost and limited coverage in bridge structure damage monitoring, and achieves efficient and lightweight monitoring and risk early warning.

CN120724165BActive Publication Date: 2026-05-08内蒙古自治区交通运输科学发展研究院 +2
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Patent Information

Application Number
CN202510598298.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-05-09
Publication Date
2026-05-08
Estimated Expiration
2045-05-09

AI Technical Summary

Technical Problem

Existing bridge structural damage monitoring technologies are costly, have limited coverage, and low sensor utilization, making it difficult to achieve lightweight and efficient real-time diagnosis.

Method used

A method based on line-surface information fusion is adopted to acquire strain data through locally encrypted fiber optic sensors. By combining sparse optimization and Gaussian process regression, a damage feature matrix is ​​constructed, and a structural damage threshold is established using kernel density estimation, thereby realizing lightweight monitoring of bridge structures.

Benefits of technology

It improves sensor monitoring efficiency, enhances the accuracy and robustness of bridge structural damage diagnosis, and enables lightweight structural health monitoring and risk warning.

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Abstract

The application discloses a kind of beam bridge structure damage diagnosis methods based on line-surface information fusion, the method utilizes distributed optical fiber to collect beam bridge sparse measuring point information, and the strain data set of non-encryption and encryption area is obtained by encrypting key section;Using the method of sparse optimization, the data collected is denoised, the way of introducing Gaussian process regression combined with space kernel is used, the strain data of non-encryption area is used to extend and reconstruct the monitoring data of encryption area, and the strain data of the whole monitoring area is obtained;After obtaining the strain data, the strain data correlation coefficient in different time domain is calculated, and the damage feature matrix is constructed;By solving the Frobenius norm of correlation matrix, the structure damage threshold is established by using kernel density estimation method, and the effective early warning of bridge structure risk is realized.The method can improve the monitoring efficiency of sensor, realize the lightweight structure health monitoring, and provide effective protection for the safe operation and maintenance of bridge structure in operation period.
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