Parameter identification for structural health monitoring based on Monte Carlo method and likelihood estimate
Parameter identification for structural health monitoring based on Monte Carlo method and likelihood estimate
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基于蒙特卡罗方法和似然估计的结构健康监测参数辨识
DOI：
10.1177/1550147718786888
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发表时间：
2018
影响因子：
2.3
通讯作者：
Wan Chunfeng
中科院分区：
文献类型：
--
作者：
Xue Songtao;Wen Bo;Huang Rui;Huang Liyuan;Sato Tadanobu;Xie Liyu;Tang Hesheng;Wan Chunfeng
结构参数是反映结构性能和状况的最重要因素。因此，它们的识别成为结构健康监测的结构评估和损伤识别最重要的方面。本文提出了一种基于蒙特卡罗方法和似然估计的结构参数识别方法。由此，可以识别和研究诸如刚度和阻尼之类的参数。研究并比较了无噪声、高斯噪声和非高斯噪声三种不同条件下的识别效果。考虑到损伤的存在，损伤识别也是通过结构参数的识别来实现的。进行了仿真和实验来验证所提出的方法。结果表明，可以很好地识别结构参数以及损坏情况。此外，所提出的方法对噪声具有很强的鲁棒性。所提出的方法对于实际结构健康监测的应用具有前景。
Structural parameters are the most important factors reflecting structural performance and conditions. As a result, their identification becomes the most essential aspect of the structural assessment and damage identification for the structural health monitoring. In this article, a structural parameter identification method based on Monte Carlo method and likelihood estimate is proposed. With which, parameters such as stiffness and damping are identified and studied. Identification effects subjected to three different conditions with no noise, with Gaussian noise, and with non-Gaussian noise are studied and compared. Considering the existence of damage, damage identification is also realized by the identification of the structural parameters. Both simulations and experiments are conducted to verify the proposed method. Results show that structural parameters, as well as the damages, can be well identified. Moreover, the proposed method is much robust to the noises. The proposed method may be prospective for the application of real structural health monitoring.