Bridge equivalent vehicle load model construction method and system based on fatigue cumulative damage

Through bridge traffic monitoring and model construction, a probability function model is generated, which solves the problem of fatigue cumulative damage in bridge design and improves the accuracy and safety of bridge safety assessment.

CN120354512BActive Publication Date: 2025-10-17JIANGXI VANDT COLLEGE OF COMM
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Patent Information

Application Number
CN202510848763.X
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-06-24
Publication Date
2025-10-17
Estimated Expiration
2045-06-24

AI Technical Summary

Technical Problem

Existing bridge design specifications fail to effectively consider the cumulative fatigue damage caused by the large-scale and heavy-loaded freight trucks, resulting in inaccurate safety assessments and ignoring the cumulative effects of fatigue damage.

Method used

Vehicle load data is obtained through bridge traffic monitoring, preprocessed and distribution law analyzed, a probability function model is generated, a fatigue vehicle load model is constructed, and model verification and optimization adjustments are performed to generate an optimized fatigue damage model for multi-scenario application deployment.

Benefits of technology

The accuracy of bridge safety assessment is improved, the bridge safety reserve is made more consistent with the actual situation, and the safety of the bridge is enhanced through the cumulative effect of fatigue damage.

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Abstract

The embodiment of the present application relates to the technical field of bridge safety, and specifically discloses a bridge equivalent vehicle load model construction method and system based on fatigue cumulative damage. The embodiment of the present application acquires vehicle load data by performing bridge traffic monitoring; performs distribution law analysis and probability fitting to generate a probability function model; constructs a fatigue vehicle load model; simplifies the model into an equivalent fatigue damage model; performs model verification and optimization adjustment on the equivalent fatigue damage model to generate an optimized fatigue damage model; and performs multi-scenario application deployment. Load monitoring, analysis and probability fitting can be performed to generate a probability function model, fatigue damage evaluation and model simplification are then performed to construct an equivalent fatigue damage model, model verification and optimization adjustment are then performed to generate an optimized fatigue damage model, and multi-scenario application deployment is then performed, so that the bridge safety reserve is more in line with actual conditions, and the accuracy of bridge safety evaluation is improved through the cumulative effect of fatigue damage.
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