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Wavelet Entropy Measure Definition and Its Application for Transmission Line Fault Detection and Identification (Part I: Definition and Methodology)

机译:小波熵测量定义及其用于传输线故障检测和识别的应用(第一部分:定义和方法)

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Shannon entropy in time domain can measure signal or system uncertainty. Spectrum entropy based on Shannon entropy can be taken as a measure of signal or system complexity. Use for reference, wavelet entropy measures built on wavelet analysis can signify the complexity of unsteady signal or system in both time domain and frequency domain. Beginning with the thought of information mergence and post-analysis in this paper, fundamental definitions of wavelet entropy measure are discussed, calculation methods including wavelet energy entropy, wavelet time entropy, wavelet singular entropy, wavelet time frequency entropy, wavelet average entropy and wavelet distance entropy are put forward, and their physical meanings are analyzed. Considering wavelet entropy measure applied well in field of EEG signal and mechanical fault diagnosis, the potential and approach that it is applied in transmission line fault detection and identification are analyzed.
机译:Shannon熵在时域可以测量信号或系统不确定性。基于Shannon熵的频谱熵可以作为信号或系统复杂性的度量。用于参考,基座上基于小波分析的小波熵测量可以在时间域和频域中表示不稳定信号或系统的复杂性。从思想开始思考并在本文的分析后,讨论了小波熵措施的基本定义,计算方法包括小波能量熵,小波时间熵,小波奇异熵,小波时频熵,小波平均熵和小波距离提出了熵,分析了它们的物理意义。考虑到eEG信号和机械故障诊断领域的小波熵测量,分析了它在传输线故障检测和识别中应用的电位和方法。

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