基于桥梁原位流场数据的旋涡脱落智能识别与追踪方法

By using intelligent identification and tracking methods based on in-situ flow field data of bridges, the problem of low accuracy in identifying vortex shedding in bridges has been solved, achieving high-precision identification and tracking of vortex shedding, and improving the wind resistance safety and economy of bridges.

CN120651478BActive Publication Date: 2026-07-17SOUTHEAST UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SOUTHEAST UNIV
Filing Date
2025-06-13
Publication Date
2026-07-17

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Abstract

本发明公开了一种基于桥梁原位流场数据的旋涡脱落智能识别与追踪方法，具体包括：通过协同激光雷达和风速仪采集桥梁全域流场数据，据此反演流场特性参数，识别旋涡结构并进行特征提取，进而得到涡脱特征参数，结合深度集成学习算法，构建流场特性参数与涡脱特征参数的映射关系，建立桥梁涡脱智能识别模型；在此基础上，构建涡脱轨迹时空演化图谱，分析“风速梯度‑涡脱强度”的映射关系，建立涡脱失稳预测模型。该方法可有效识别和追踪桥梁原位涡脱现象，进一步提升桥梁抗风智能化水平。
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