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Frequency mode identification using modified masking signal-based empirical mode decomposition

机译:使用基于屏蔽信号的经验模式分解的频率模式识别

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摘要

A modified masking empirical mode decomposition (EMD) for effectively improving the mode separation capability of standard EMD while analysing power system signals with closely spaced modes of frequency is proposed here. A multi-frequency test signal resembling the dynamic power system signal and the actual data recorded by wide area measurement systems (WAMS) from Northern Grid, India, on 1 June 2010 due to generation loss are analysed by both the existing method and the proposed method. Various components of modal frequency extracted by masking signal base EMD are compared with extracted components by the proposed modified masking EMD. Further, the time-frequency representation of extracted modes by Hilbert spectral analysis is implemented to know mode behaviour with time reference. Simulation results prove that the EMD with proposed modification is capable of separating various modes of frequencies present in the WAMS signal.
机译:本文提出了一种改进的掩蔽经验模式分解(EMD),可以有效地提高标准EMD的模式分离能力,同时分析具有紧密间隔的频率模式的电力系统信号。通过现有方法和拟议方法,分析了类似于动态电力系统信号的多频测试信号和由印度北部电网在2010年6月1日记录的实际数据,该数据来自印度北部电网,由于发电损耗。将通过掩蔽信号库EMD提取的模态频率的各个分量与通过提出的改进掩蔽EMD提取的分量进行比较。此外,通过希尔伯特频谱分析实现了提取模式的时频表示,以了解具有时间基准的模式行为。仿真结果证明,经过改进的EMD能够分离WAMS信号中存在的各种频率模式​​。

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