基于扩展卡尔曼估计算法的地震模拟振动台模型识别

发布时间：2018-02-27 22:47

本文关键词： 模型更新结构参数识别地震模拟振动台扩展卡尔曼滤波估计　出处：《振动与冲击》2014年12期 　论文类型：期刊论文

【摘要】：由于地震模拟振动台的长期使用和多次维护,其实际工作中的模型往往难以建立,而地震模拟振动台模型的修正对于估计实验结构底部剪力有重要作用。为此利用扩展卡尔曼估计算法识别了哈尔滨工业大学地震模拟振动台模型。首先,对一单自由度结构进行仿真,通过测量位移响应,将结构参数准确的识别。随后,对抗震实验室振动台进行了3次空台加载,通过测量振动台台面位移,利用扩展的卡尔曼估计算法,识别地震模拟振动台的模型,更新了其质量,阻尼和刚度。而后分别进行两组不同载荷形成的空台加载实验,由识别参数重构计算得到的台面响应与实测台面响应吻合良好,由此表明振动台模型参数估计准确。通过此次研究既可以有效的认识不同构建形式的振动台模型,同样也可用于确定某些难以测得参数的复杂结构的模型。
[Abstract]:Because of the long-term use and maintenance of the shaking table in earthquake simulation, it is often difficult to establish the model in practical work. The modification of seismic simulation shaking table model plays an important role in estimating the shear force at the bottom of the experimental structure. Therefore, an extended Kalman estimation algorithm is used to identify the seismic simulation shaking table model of Harbin University of Technology. A single degree of freedom structure is simulated, and the structural parameters are accurately identified by measuring the displacement response. Then, three empty table loads are carried out on the shaking table of the earthquake resistant laboratory, and the displacement of the shaking table is measured by measuring the displacement of the shaking table. Using the extended Kalman estimation algorithm, the model of the shaking table is identified, and its mass, damping and stiffness are updated. The calculated results from the reconstruction of identification parameters are in good agreement with the measured ones, which indicates that the parameters of the shaking table model can be estimated accurately. It can also be used to determine complex structures with difficult parameters.
【作者单位】：哈尔滨工业大学土木工程学院;
【基金】：国家自然科学基金(51161120360) 哈尔滨工业大学创新基金(01319406)
【分类号】：TU317

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