项目名称: 车载激励下基于自适应滤波方法的桥梁结构在线监测与损伤识别研究
项目编号: No.51268045
项目类型: 地区科学基金项目
立项/批准年度: 2013
项目学科: 建筑科学
项目作者: 张纯
作者单位: 南昌大学
项目金额: 50万元
中文摘要: 在线监测桥梁结构状态、识别局部损伤对于保障在役桥梁安全性意义重大。由于以行驶车辆作为激励源特别适于桥梁结构的激振,且具有不中断交通等优点,因此本申请项目将以扩展卡尔曼滤波方法为基础,采取整体结构参数监测与局部子结构损伤识别相结合的策略,研究车载激励下桥梁结构的在线监测与损伤识别问题。主要研究内容为:针对车桥耦合系统参数识别问题建立缩减自由度形式的扩展卡尔曼滤波算法;引入桥梁结构广义坐标稀疏性的约束条件改善卡尔曼递推算法收敛性;为适应车桥耦合系统响应及噪声的时变特性,采用自适应技术自动调整递推算法及状态预测和测量方程中的误差协方差矩阵;分析测点数目、布置等因素对参数识别精度的影响;利用有限测点的时程信号重构桥梁整体运动状态及修正结构参数,判断局部损伤的可能性,并构建相应的子结构边界条件,利用子结构测点的时程响应完成桥梁结构损伤识别。本申请项目研究成果可为桥梁结构安全状况评估提供有效技术。
中文关键词: 卡尔曼滤波;车桥耦合振动;损伤识别;正则化方法;有限测量设备
英文摘要: The on-line health monitoring and local damage identification of bridges are becoming more important in maintaining the security of service bridges. For large civil structures such as long-span bridges, the passing vehicles are more suitable as excitation sources than impulsive or sinusoidal loads and the corresponding detection method will not influence the normal bridge operation. Based on extended Kalman filtering method, the on-line health monitoring and damage detection methods are studied using operating vehicle load with the diagnosis strategy combining the parameters detection of whole structure and damage identification of substructure in this research application. The research will concludes the following contents. The extended Kalman filtering method considering the bridge model with reduced degree of freedoms is established according to the analysis of bridge-vehicle coupled vibration, and the constraints of the sparsest generalized coordinates are introduced into the Kalman recursive algorithm. In order to adapt time-varying features of the bridge-vehicle coupled system, the adaptive adjusting technique is used to update the recursive algorithm and the noise covariance of the process and the measurement adaptively. While the dynamical responses of whole bridge are reconstructed and the parameters of
英文关键词: Kalman filter;couple vibration of vehicle and bridge;damage identification;regularization method;limit measurement equipment