Tsallis Wavelet Entropy and Its Application in Power  Signal Analysis

Chen, Jikai; Li, Guoqing

doi:10.3390/e16063009

Cited by 56 publications

(28 citation statements)

References 18 publications

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“…It reduces accuracy of feature extraction and could cause that feature extraction is submerged in the background noise [30]. Due to adjustable parameter α of Renyi, based on the feature of measured signals, α is adjusted to reduce the effect of wavelet aliasing on accuracy of feature extraction.…”

Section: Contrastanalysisof Rwpe and Swpementioning

confidence: 99%

A Transient Fault Recognition Method for an AC-DC Hybrid Transmission System Based on MMC Information Fusion

Chen

Dou

et al. 2016

Energies

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At present, the research is still in the primary stage in the process of fault disturbance energy transfer in the multilevel modular converter based high voltage direct current (HVDC-MMC). An urgent problem is how to extract and analyze the fault features hidden in MMC electrical information in further studies on the HVDC system. Aiming at the above, this article analyzes the influence of AC transient disturbance on electrical signals of MMC. At the same time, it is found that the energy distribution of electrical signals in MMC is different for different arms in the same frequency bands after the discrete wavelet packet transformation (DWPT). Renyi wavelet packet energy entropy (RWPEE) and Renyi wavelet packet time entropy (RWPTE) are proposed and applied to AC transient fault feature extraction from electrical signals in MMC. Using the feature extraction results of Renyi wavelet packet entropy (RWPE), a novel recognition method is put forward to recognize AC transient faults using the information fusion technology. Theoretical analysis and experimental results show that the proposed method is available to recognize transient AC faults.

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Section: Contrastanalysisof Rwpe and Swpementioning

confidence: 99%

A Transient Fault Recognition Method for an AC-DC Hybrid Transmission System Based on MMC Information Fusion

Chen

Dou

et al. 2016

Energies

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“…It also has been applied in power systems for quite a long time [27][28][29]. Since a more chaotic signal generates greater entropy, the energy distribution of a certain frequency band, which is represented by a set of wavelet details, can be regarded as a dynamic system.…”

Section: Definition Of Wavelet Entropymentioning

confidence: 99%

Recognition of Traveling Surges in HVDC with Wavelet Entropy

Luo

Lin

Zhou

et al. 2017

Entropy

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Abstract:Traveling surges are commonly adopted in protection devices of high-voltage direct current (HVDC) transmission systems. Lightning strikes also can produce large-amplitude traveling surges which lead to the malfunction of relays. To ensure the reliable operation of protection devices, recognition of traveling surges must be considered. Wavelet entropy, which can reveal time-frequency distribution features, is a potential tool for traveling surge recognition. In this paper, the effectiveness of wavelet entropy in characterizing traveling surges is demonstrated by comparing its representations of different kinds of surges and discussing its stability with the effects of propagation distance and fault resistance. A wavelet entropy-based recognition method is proposed and tested by simulated traveling surges. The results show wavelet entropy can discriminate fault traveling surges with a good recognition rate.

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“…In order to research effect of wavelet aliasing on feature extraction accuracy of the SWE and SWPE, Shannon wavelet energy entropy (SWEE) is as an example to analyze the relationship between the wavelet energy leakage and the accuracy of feature extraction [34].…”

Section: Wavelet Aliasing Effect On Swe and Swpementioning

confidence: 99%

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

Chen

Dou

et al. 2016

Entropy

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Abstract: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.

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Tsallis Wavelet Entropy and Its Application in Power Signal Analysis

Cited by 56 publications

References 18 publications

A Transient Fault Recognition Method for an AC-DC Hybrid Transmission System Based on MMC Information Fusion

A Transient Fault Recognition Method for an AC-DC Hybrid Transmission System Based on MMC Information Fusion

Recognition of Traveling Surges in HVDC with Wavelet Entropy

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

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