Identification of Hysteretic Dynamic Systems by Using Hybrid Extended Kalman Filter and Wavelet Multiresolution Analysis with Limited Observation
Identification of Hysteretic Dynamic Systems by Using Hybrid Extended Kalman Filter and Wavelet Multiresolution Analysis with Limited Observation
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DOI：
10.1061/(asce)em.1943-7889.0000510
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发表时间：
2013-05
期刊：
影响因子：
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通讯作者：
Hui Li;C. Mao;J. Ou
中科院分区：
文献类型：
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作者：
Hui Li;C. Mao;J. Ou
摘要 非线性滞回系统识别方法的可用性对于强震期间和震后民用基础设施的健康评估和修复至关重要。然而，大多数用于识别迟滞系统的方法都存在两个问题：（1）必须测量所有动态自由度（DOF）的结构响应，这对于实际应用显然是不切实际的； (2)假设系统的非线性模型是已知的，仅需要识别模型参数，这意味着可能无法准确捕获底层结构的非线性特性。为了克服这两个问题，本文提出了一种新方法，该方法不假设非线性模型，并且不需要在所有自由度上进行测量。新方法交替使用扩展卡尔曼滤波器（EKF）和小波（W）多分辨率分析。在每个时间步内，识别可以分为两个阶段。在第一阶段，巴...
AbstractThe availability of methods for the identification of nonlinear hysteretic systems is crucial for the assessment of the health and the repair of civil infrastructures during and after severe earthquakes. However, most methods used to identify hysteretic systems suffer from two problems: (1) the structural responses at all dynamic degrees of freedom (DOFs) must be measured, which is obviously impractical for real applications; and (2) the nonlinear model of a system is assumed to be known, and only the model parameters are to be identified, meaning that the nonlinear characteristics of the underlying structures may not be captured accurately. To overcome these two problems, this paper proposes a novel method that does not assume a nonlinear model and that does not require measurements at all DOFs. The new approach alternately uses the extended Kalman filter (EKF) and wavelet (W) multiresolution analysis. Within each time step, the identification can then be divided into two stages. In stage one, ba...