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Application of Shannon Wavelet Entropy and Shannon Wavelet Packet Entropy in Analysis of Power System Transient Signals

机译:香农小波熵和香农小波包熵在电力系统暂态信号分析中的应用

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In a power system, the analysis of transient signals is the theoretical basis of fault diagnosis and transient protection theory. Shannon wavelet entropy (SWE) and Shannon wavelet packet entropy (SWPE) are powerful mathematics tools for transient signal analysis. Combined with the recent achievements regarding SWE and SWPE, their applications are summarized in feature extraction of transient signals and transient fault recognition. For wavelet aliasing at adjacent scale of wavelet decomposition, the impact of wavelet aliasing is analyzed for feature extraction accuracy of SWE and SWPE, and their differences are compared. Meanwhile, the analyses mentioned are verified by partial discharge (PD) feature extraction of power cable. Finally, some new ideas and further researches are proposed in the wavelet entropy mechanism, operation speed and how to overcome wavelet aliasing.
机译:在电力系统中,暂态信号的分析是故障诊断和暂态保护理论的理论基础。香农小波熵(SWE)和香农小波包熵(SWPE)是用于瞬态信号分析的强大数学工具。结合有关SWE和SWPE的最新成就,总结了它们在瞬态信号特征提取和瞬态故障识别中的应用。对于小波分解相邻尺度上的小波混叠,分析了小波混叠对SWE和SWPE特征提取精度的影响,并比较了它们之间的差异。同时,通过电力电缆的局部放电(PD)特征提取验证了上述分析。最后,提出了关于小波熵机制,运算速度以及如何克服小波混叠的一些新思路和进一步的研究。

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