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Identification of Modal Parameters for Close-mode Structures with Output-only Data

机译:仅输出数据的闭模结构模态参数的识别

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摘要

A time domain method to directly separate system modes from spurious modes for close-mode structure with output-only data is presented in the paper. The time series analysis is often adopted for identifying structural dynamic characteristics in time domain with output-only data. However, the problems caused by spurious mode contradict its application to close-mode structures. According to the equivalent relationship between system equation of motion and state equation of output vector, the backward differential model of the correlation function is formulated with output-only data. Based on the location relationship between the unit circle and the eigen-values on the complex plane, a method to determine the system modes is proposed. The system modal parameters are then calculated by the system eigen-values and eigen-vectors of the characteristic matrix of the backward differential model. To verify the validity of the proposed method, numerical simulations of the Kabe’s mass-spring model, which is a typical close-mode system, have been carried out with output-only data. The results indicate the feasibility of using the present method in the modal identification for close-mode structures with output-only data.
机译:本文提出了一种时域方法,可将仅输出数据的密闭模式的系统模式与杂散模式直接分离。通常采用时间序列分析来通过仅输出数据来识别时域中的结构动力特性。但是,由杂散模式引起的问题与它在封闭模式结构中的应用矛盾。根据运动的系统方程与输出矢量的状态方程之间的等效关系,用仅输出数据来构造相关函数的后向微分模型。基于单位圆与特征平面上特征值之间的位置关系,提出了一种确定系统模式的方法。然后,通过后向微分模型的特征矩阵的系统特征值和特征向量计算系统模态参数。为了验证所提出方法的有效性,已经对Kabe质量弹簧模型进行了数值模拟,该模型是典型的封闭模式系统,仅使用输出数据进行了仿真。结果表明,在仅输出数据的闭模结构的模态识别中使用本方法的可行性。

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