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An improved Hilbert Vibration Decomposition method for analysis of low frequency oscillations

机译:一种改进的希尔伯特振动分解方法,用于分析低频振荡

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In this paper, a masking-based Hilbert Vibration Decomposition (HVD) method is proposed to analyze nonlinear and non-stationary power system data. An adaptive masking signal method derived from the data itself is used to improve the decomposition ability of the HVD method. Techniques to compute the masking signal are described and precise criteria to increase the modal resolution of the HVD method are derived. Simulation results using both synthetic and simulated data show that the technique can be used to characterize complex oscillatory processes in power systems.
机译:本文提出了一种基于掩蔽的希尔伯特振动分解(HVD)方法来分析非线性和非平稳电力系统数据。从数据本身派生的自适应掩蔽信号方法用于提高HVD方法的分解能力。描述了计算掩蔽信号的技术,并得出了提高HVD方法的模态分辨率的精确标准。使用合成和仿真数据进行的仿真结果表明,该技术可用于表征电力系统中的复杂振荡过程。

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