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• W2771936398 abstract "The insulation deterioration of mining dry-type transformer is always accompanied with partial discharge (PD). The assessment accuracy of transformer insulation performance is directly affected by the authenticity of the PD signal. Based on the ensemble empirical mode decomposition (EEMD) and combining the principle of higher order statistics, a hybrid method for suppressing white noise in PD signals was proposed. First, the PD signals were decomposed into a number of intrinsic mode function (IMF) components. Then the signal's Gaussian components were detected and removed by kurtosis as gaussianity estimators supplemented by bootstrap techniques. The white noise in the components were suppressed through thresholding and reconstructing each IMF with adaptive thresholds. Finally, the results were reconstructed and return to the original signal. The validity of this method is proved by simulated signals and practical PD signals." @default.
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• W2771936398 date "2017-01-01" @default.
• W2771936398 modified "2023-09-25" @default.
• W2771936398 title "Partial discharge of white noise suppression method based on EEMD and higher order statistics" @default.
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• W2771936398 doi "https://doi.org/10.1049/joe.2017.0688" @default.
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