首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part C. Journal of mechanical engineering science >Prediction of random dynamic loads using second-order blind source identification algorithm
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Prediction of random dynamic loads using second-order blind source identification algorithm

机译:使用二阶盲源识别算法预测随机动态载荷

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摘要

Traditional load identification methods are based on the frequency response function matrix. However, in some cases, it is impossible to measure the frequency response functions directly, where only the measured structural dynamic response data are available. In this paper, a novel frequency domain method based on second-order blind source identification (SOBI) algorithm is proposed for identifying the random dynamic loads from some dynamic responses of limited test points. Firstly, the SOBI algorithm is applied to identify the modal parameters from the time histories of the measured displacement responses and then the modal loads are estimated by the identified modal parameters and modal responses in the modal space; finally, the random dynamic loads can be identified in the frequency domain. In order to control the error propagation, the theoretical formulas of the regularization process have been deduced, and the regularization parameters are selected by the generalized cross-validation method. A numerical simulation and an eight-storey spatial frame experimental model are studied to validate the proposed method; the comparison results show a good agreement between the identified random dynamic loads and the actually exerted loads.
机译:传统的负载识别方法基于频率响应函数矩阵。然而,在某些情况下,不可能直接测量频率响应函数,其中仅获得测量的结构动态响应数据。本文提出了一种基于二阶盲源识别(SOBI)算法的新频域方法,用于识别来自有限测试点的某些动态响应的随机动态载荷。首先,应用SOBI算法来识别来自测量的位移响应的时间历史的模态参数,然后通过识别的模态参数和模态空间中的模态响应估计模态负载;最后,可以在频域中识别随机动态负载。为了控制误差传播,已经推断了正则化过程的理论公式,并通过广义交叉验证方法选择正则化参数。研究了数值模拟和八层空间框架实验模型,以验证提出的方法;比较结果显示了所识别的随机动态负载和实际施加的负载之间的良好一致性。

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