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为实现复杂杆系结构损伤位置定位与损伤程度预测，提出了一种基于数据驱动损伤档案的损伤识别方法。通过识别指标、分区域两步识别和网络训练三方面介绍损伤档案的识别流程；通过数值模拟建立大型桁架桥结构的有限元模型，并利用均匀设计法建立区域损伤库和区域内构件损伤库；通过对网络进行训练，识别构件的损伤位置和损伤程度。桁架桥数值模拟结果表明，损伤位置定位准确，损伤程度识别误差在5%以内。
Abstract：In order to realize damage location and damage degree prediction of complex truss structures,a data-driven damage file-based damage identification method is proposed.The process of damage file recognition is introduced from three aspects:recognition index,two-step recognition by subregion and network training.The finite element model of large truss bridge structure is established through numerical simulation,and the regional damage reservoir and the regional internal component damage reservoir are established by using the uniform design method.By training the network,the damage location and damage degree of the component are identified.The numerical simulation results of truss bridge show that the damage is accurately located and the error of damage degree identification is less than 5%.
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基本信息:
中图分类号:TU317;TU323
引用信息:
[1]谭凯旋,张光槟,付伟庆.基于数据驱动损伤档案的复杂杆系结构损伤识别方法[J].青岛理工大学学报,2025,46(06):11-17.
基金信息:
国家自然科学基金(52178488); 山东省自然科学基金(ZR2025MS932)