基于动力指纹的斜拉桥桥塔冲刷深度识别方法

提出了一种基于动力指纹的斜拉桥桥塔冲刷深度识别方法.利用理论分析得到不同冲刷深度与所提出的动力指纹之间的定量关系;进而在常规桥梁检测中得到桥梁野外状态下的动力特性实测数据,通过反演分析利用预先得到的定量关系最终得到对应的桥塔冲刷深度.为研究该方法的适用性与可行性,分别提出全桥固有频率以及模态柔度位移两种动力指纹构成形式,并基于宁波招宝山大桥(斜拉桥),采用数值仿真的手段,分析两种动力指纹与冲刷深度之间的定量关系特征.分析结果表明:通过跟踪两种动力指纹变化情况,均可较好地对斜拉桥桥塔冲刷深度进行定量识别;特别采用主梁竖弯振型或主塔横弯振型构建模态柔度位移指标时可得到更为敏感的冲刷识别效果.该方法可借助常规桥梁检测项目对桥塔冲刷状态完成定性判断及定量分析,具备计算逻辑严密、监测设备经济性好、完全避免水下操作等特点,在上部结构动力特征正确识别的基础上,可实现斜拉桥桥塔冲刷深度的准确预测.

Identification Method for Pylon Scour Depth of Cable-stayed Bridges by Tracing Dynamic Index

This paper proposed an identifying method of scour condition of cable-stayed bridge pylon by tracing the dynamic index. Firstly the quantitative relationship between the identification index and scour depth is theoretically simulated by a series of parametric study. Once the identification index is obtained based on the monitored dynamic performances during the bridge routine measurement,the scour depth of pylons at the moment of monitoring can be directly deduced by the pre-obtained quantitative relationship. In order to investigate the feasibility of this method,two identification indexes such as the natural frequency of bridge and deformation of modal flexibility were proposed. As a case study,the relationships between these two identification indexes and scour depth of pylon were carefully analyzed based on Finite Element (FE) model of Ningbo Zhaobaoshan bridge (a cable-stayed bridge). The results indicate that the pylon scour depth of cable-stayed bridges can be quantitatively identified by tracing the identification indexes. Especially,the indexes including the deformation of modal flexibility built by the vibration modes of vertical bending of girder and transverse bending of pylon show much more sensitive and better identification effects than those of other indexes. It can be concluded that the proposed identifying method for pylon scour depth by tracing the dynamic index has the advantages of accurate calculation logic,convenience,and good economical efficiency without underwater operation. The scour depth can be correctly predicted as long as the dynamic performances of bridges are accurately measured and traced.