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Structural damage identification based on parameter identification using Monte Carlo method and likelihood estimation

机译:基于参数识别的蒙特卡洛方法和似然估计的结构损伤识别

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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 paper, 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 results subjected to three different conditions of without noise, with Gaussian noise and with non-Gaussian noise are studied and compared. Considering the existence of damage, damage identification is also realized through the identification of 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.
机译:结构参数是反映结构性能和条件的最重要因素。结果,它们的识别成为结构评估和结构健康监测中损坏识别的最重要方面。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。通过这些参数,可以识别和研究诸如刚度和阻尼的参数。研究并比较了在三种不同条件下无噪声,高斯噪声和非高斯噪声的识别结果。考虑到损伤的存在,通过结构参数的识别也可以实现损伤的识别。仿真和实验都进行了验证该方法。结果表明,可以很好地识别结构参数以及损伤。而且,所提出的方法对噪声非常鲁棒。所提出的方法对于实际结构健康监测的应用可能具有前瞻性。

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