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• W2072581623 abstract "Ensemble Empirical Mode Decomposition (EEMD) can overcome the mode mixing problem in Empirical Mode Decomposition (EMD) effectively. The Hilbert-Huang transform still exists end effect in applications, in order to improve the end effect, this paper put forward a method of fault feature extraction based on improved EEMD and Hilbert transform which combines support vector regression (SVR) machine with mirror extension to continue the signal. The analysis on simulation experiments results show that the method can restrain the end effect effectively, get a more accurate instantaneous frequency and instantaneous amplitude." @default.
• W2072581623 created "2016-06-24" @default.
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• W2072581623 date "2011-08-01" @default.
• W2072581623 modified "2023-10-18" @default.
• W2072581623 title "Fault Feature Extraction Based on Improved EEMD and Hilbert Transform" @default.
• W2072581623 cites W2012124587 @default.
• W2072581623 cites W2029956212 @default.
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• W2072581623 doi "https://doi.org/10.4028/www.scientific.net/amr.314-316.1126" @default.
• W2072581623 hasPublicationYear "2011" @default.
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