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A frequency domain blind identification method for operational modal analysis using a limited number of sensors

机译:使用有限数量的传感器进行操作模态分析的频域盲识别方法

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摘要

Operational modal analysis is an experimental modal analysis approach, which uses vibration data collected when the structure is under operating conditions. Amongst the methods for operational modal analysis, blind source separation-based methods have been shown to be efficient and powerful. The existing blind source separation modal identification methods, however, require the number of sensors to be at least equal to the number of modes in the frequency range of interest to avoid spatial aliasing. In this article, a frequency domain algorithm that overcomes this problem is proposed, which is based on the joint diagonalization of a set of weighted covariance matrices. In the proposed approach, the frequency range of interest is partitioned into several frequency ranges in which the number of active modes in each band is less than the number of sensors. Numerical simulations and an experimental example demonstrate the efficacy of the method.
机译:操作模态分析是一种实验模态分析方法,它使用当结构在操作条件下时收集的振动数据。 在操作模态分析的方法中,已显示盲源分离的方法是有效和强大的。 然而,现有的盲源分离模态识别方法要求传感器的数量至少等于频率范围内的模式的数量,以避免空间混叠。 在本文中,提出了一种克服该问题的频域算法,其基于一组加权协方差矩阵的联合对角化。 在所提出的方法中,频率范围被划分为几个频率范围,其中每个频带中的有源模式的数量小于传感器的数量。 数值模拟和实验例证明了该方法的功效。

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