基于经验模态分解的旋转叶片特征分析

Mickael Bruno, A. Balleri
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引用次数: 0

摘要

在本文中,我们介绍了一个实验试验的结果,从一个目标的旋转叶片在x波段进行数据收集。我们将经验模态分解(EMD)应用于实验数据,并通过研究目标固有模态函数(IMF)相对于实验基础真值的自相关特性,研究其所包含的信息作为叶片转速的函数。为了了解IMFs作为信噪比(SNR)的函数是如何变化的,实验结果与一组模拟相辅相成。结果表明,EMD可以提供叶片角速度的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of the signature of rotating blades with the Empirical Mode Decomposition
In this paper, we present the results of an experimental trial carried out to collect data from a target with a rotating blade at X-band. We apply the Empirical Mode Decomposition (EMD) to the experimental data and we investigate the information contained in the target Intrinsic Mode Functions (IMF) as a function of the blade speed of rotation, by studying their auto-correlation properties with respect to the experimental ground truth. Experimental results are complimented by a set of simulations in order to understand how the IMFs change as a function of Signal to Noise Ratio (SNR). Results show that the EMD can provide information on the angular speed of the blade.
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