摘要
基于广义卡尔曼滤波提出了随机荷载作用下桥梁结构物理参数的识别方法。首先,以荷载为观测对象,推导出基于有限元模型的桥梁结构系统的观测方程,以结构待识别的物理参数为状态向量,建立系统状态方程;然后,对该状态方程和观测方程构成的非线性参数系统应用广义卡尔曼滤波,从而识别出结构的物理参数。对一座简支梁桥和一座三跨连续梁桥在不同工况下的物理参数识别进行了数值仿真,结果表明本文方法能够准确地识别桥梁结构全部刚度参数、质量参数和阻尼参数,且具有很强的抗噪性能,从而验证了本文方法的有效性和鲁棒性,可应用于识别大型桥梁结构的物理参数。
Based on the extended Kalman filter, an identification method on physical parameters of bridge structures subjected to stochastic loads is proposed. Taking the loads as observation objects, the observation equation based on finite element model of bridge structures is derived. Taking the unknown physical parameters of the structure as state variables, the state equation of system is established. Employing the extended Kalman filter algorithm to the nonlinear parametric system formulated by the state equation and the observation equation, the physical parameters of the structure are identified. For verification purposes, the identification on the physical parameters of a simply supported beam bridge and a 3-span continuous beam bridge are numerically simulated under different cases. The results show that the stiffness, mass and damping parameters of bridge structures can be identified by the proposed method with high accuracy and strong noise resistance feature. This proves the effectiveness and robustness of the proposed method, which can be applied for the identification on physical parameters of large bridge structures.
出处
《计算力学学报》
EI
CAS
CSCD
北大核心
2007年第4期472-476,共5页
Chinese Journal of Computational Mechanics
基金
国家杰出青年科学基金(50425824)资助项目
关键词
桥梁结构
物理参数
识别
广义卡尔曼滤波
有限元
随机荷载
bridge structures
physical parameter
identification
extended Kalman filterfinite element
stochastic load
