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Output-Only Nonlinear Finite Element Model Updating Using Autoregressive Process

机译:基于自回归过程的纯输出非线性有限元模型更新

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A novel approach to deal with nonlinear system identification of civil structures subjected to unmeasured excitations is presented. Using only sparse global dynamic structural response, mechanics-based nonlinear finite element (FE) model parameters and unmeasured inputs are estimated. Unmeasured inputs are represented by a time-varying autoregressive (TAR) model. Unknown FE model parameters and TAR model parameters are jointly estimated using an unscented Kalman filter. The proposed method is validated using numerically simulated data from a 3D steel frame subjected to seismic base excitation. Six material parameters and one component of the base excitation are considered as unknowns. Excellent input and model parameter estimations are obtained, even for low order TAR models.
机译:提出了一种处理非测量激励下土木结构非线性系统辨识的新方法。仅使用稀疏全局动态结构响应,估计基于力学的非线性有限元(FE)模型参数和未测量输入。未测量的输入由时变自回归(TAR)模型表示。利用无迹卡尔曼滤波器联合估计未知的有限元模型参数和TAR模型参数。利用三维钢框架在地震基础激励下的数值模拟数据验证了该方法的有效性。六个材料参数和基础激励的一个分量被视为未知量。即使对于低阶TAR模型,也能获得很好的输入和模型参数估计。

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