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Parameter Identification For Nonlinear Behavior Of Rc Bridge Piers Using Sequential Modified Extended Kalman Filter

机译:序列修正扩展卡尔曼滤波在钢筋混凝土桥墩非线性行为参数识别中的应用

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摘要

Identification of the nonlinear hysteretic behavior of a reinforced concrete (RC) bridge pier subjected to earthquake loads is carried out based on acceleration measurements of the earthquake motion and bridge responses. The modified Takeda model is used to describe the hysteretic behavior of the RC pier with a small number of parameters, in which the nonlinear behavior is described in logical forms rather than analytical expressions. Hence, the modified extended Kalman filter is employed to construct the state transition matrix using a finite difference scheme. The sequential modified extended Kalman filter algorithm is proposed to identify the unknown parameters and the state vector separately in two steps, so that the size of the problem for each identification procedure may be reduced and possible numerical problems may be avoided. Mode superposition with a modal sorting technique is also proposed to reduce the size of the identification problem for the nonlinear dynamic system with multi-degrees of freedom. Example analysis is carried out for a continuous bridge with a RC pier subjected to earthquake loads in the longitudinal and transverse directions.
机译:基于地震运动的加速度测量和桥梁响应,对钢筋混凝土(RC)桥墩的非线性滞后行为进行了识别。修改后的Takeda模型用于描述具有少量参数的RC墩的滞后行为,其中非线性行为是以逻辑形式而不是解析表达式来描述的。因此,采用改进的扩展卡尔曼滤波器,使用有限差分方案构造状态转换矩阵。提出了顺序改进的扩展卡尔曼滤波算法,分两步分别识别未知参数和状态向量,从而可以减小每个识别过程的问题大小,并避免可能的数值问题。还提出了一种采用模态排序技术的模式叠加技术,以减小具有多个自由度的非线性动力学系统的识别问题。对具有RC墩的连续桥在纵向和横向上承受地震荷载的实例分析。

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