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首页> 外文期刊>Journal of Sound and Vibration >A maximum correntropy criterion based recursive method for output-only modal identification of time-varying structures under non-Gaussian impulsive noise
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A maximum correntropy criterion based recursive method for output-only modal identification of time-varying structures under non-Gaussian impulsive noise

机译:基于递归的递归方法,用于在非高斯脉冲噪声下的时变结构的仅输出模态识别

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摘要

This work considers the problem of output-only identification for time-varying structures in a recursive manner under non-Gaussian impulsive noise. Presently, the most existing identification methods are based on classical least-squares (LS) criterion due to its mathematical tractability, computational simplicity and optimality under Gaussian assumption. However, the performance of the LS based methods deteriorates seriously in non-Gaussian situations, especially when responses are corrupted by impulsive noise (outliers) which are frequently encountered in real test cases. To deal with this problem, a maximum correntropy criterion based recursive modal identification method is proposed in this paper, and a class of heavy-tailed alpha-stable distribution is adopted to model non-Gaussian impulsive noise. The effect of the kernel bandwidth parameter in proposed method is discussed and a rational value is given for the model structure selection. Finally, the proposed method is comparatively assessed against its LS counterpart via a numerical example and a laboratory time-varying structure experiment. The comparisons have illustrated the advantages of the proposed method on the modal frequency estimates in terms of estimation accuracy and robustness under the non-Gaussian impulsive noise. (C) 2019 Elsevier Ltd. All rights reserved.
机译:这项工作考虑了只输出识别的问题为在非高斯脉冲噪声以递归方式随时间变化的结构。目前,最现有识别方法是基于经典最小二乘(LS)准则,由于其数学易处理性,计算简单性和最优下高斯假设。然而,基于LS方法的性能严重恶化非高斯的情况下,特别是当响应由以实际测试用例经常遇到的脉冲噪声(异常)损坏。为了解决这个问题,最大correntropy准则递推模态识别方法在本文提出,以及一类重尾阿尔法稳定分布的,采用模型非高斯脉冲噪声。在提出的方法内核带宽参数的效果进行了讨论和一个合理的值,给出了模型结构的选择。最后,所提出的方法是比较通过一个数值例子和实验室随时间变化的结构实验评估针对其LS对应物。的比较已经说明上的模态频率估计所提出的方法的优点在非高斯脉冲噪声下的估计精度和稳健性方面。 (c)2019 Elsevier Ltd.保留所有权利。

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