以某自锚式悬索桥模型试验为研究背景,采用数据驱动随机子空间识别算法和改进稳定图方法对桥梁结构运营模态分析进行研究.为解决数据驱动随机子空间识别中的系统定阶和虚假模态问题,采用奇异熵增量进行系统定阶,并对稳定图进行改进,实现了虚假模态的识别与剔除,最终达到了精确识别桥梁结构模态参数的目的.采用模型试验在不同数据采集方案下的测试数据,识别该模型桥相应测试条件下的模态参数,将识别结果分别与ANSYS理论计算值、DASY-Lab模态参数识别结果进行比较,验证了所提方法及自编程序的正确性,该方法可应用于桥梁结构的运营模态分析中.%The model test of a self-anchored suspension bridge is taken as the research background, the data-driven stochastic subspace identification (Data-Driven SSI) algorithm and the improved stabilization diagram method are employed to study the operational modal analysis of bridge structure. For solving the problem of the system order determination and false modal parameters in the Data-Driven SSI, the singular entropy increment is introduced to determine the system order and to improve the stability diagram, the false modal parameters are therefore identified and eliminated and eventually the goal of accurately identifying the modal parameters of the bridge structure is attained. By using the testing data of the model test under different data acquisition cases, the modal parameters of the bridge structure Under the corresponding testing condi-tions are identified, the identified modal parameters are respectively compared to the values of the ANSYS theoretic calculation and to the results of DASYLab modal parameter identification. The correctness of the method proposed herewith and the self-complied program has been verified and the method can be applied to the operational model analysis of the bridge structure.
展开▼
