Multi-source random excitation identification for stochastic structures based on matrix perturbation and modified regularization method
Multi-source random excitation identification for stochastic structures based on matrix perturbation and modified regularization method
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DOI：
10.1016/j.ymssp.2018.09.021
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发表时间：
2019-03
影响因子：
8.4
通讯作者：
Z. C. He;Zhuomin Zhang;E. Li
中科院分区：
文献类型：
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作者：
Z. C. He;Zhuomin Zhang;E. Li
针对虚拟激励的特点以及正则化参数λ对残差范数和解范数的影响，提出了一种新的修正正则化方法来解决随机动载荷识别的不适定问题，并减小了识别误差的传播。与Moore-Penrose伪逆和Tikhonov正则化方法对测量位置选择敏感的缺点相比，改进正则化方法无论测量位置如何，都能准确、稳定地识别载荷。此外，识别的负载总是匹配的实际从低到高的频率域使用建议的修改正则化方法。将矩阵摄动法与修正正则化法相结合，分析了作用在不确定结构上的多阶载荷。通过工程实例验证了该方法的有效性和可行性。
In view of the characteristic of pseudo excitation and effects of the regularization parameter λ on the residual norm and solution norm, a novel modified regularization method is proposed to solve the ill-posed problem and mitigate the error propagation of random dynamic loads identification. Compared with Moore-Penrose pseudo inverse and Tikhonov regularization methods that are sensitive to the selection of measurement locations, the proposed modified regularization method can always identify the loads accurately and stably regardless of measurement locations. In addition, the identified loads always match the actual ones from low to high frequency domains using the proposed modified regularization method. Furthermore, the matrix perturbation method is combined with the modified regularization method to analyze the multisource loads acting on the uncertain structure. Several practical engineering examples are conducted to demonstrate that the lower and upper bounds of identified forces can be obtained, which clearly validates the effectiveness and feasibility of the proposed methods in the application of complicated structures.