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- W2780496328 abstract "This paper proposes a novel fault feature extraction method with the aim of extracting the fault feature submerged in the single-channel observation signal. The proposed method integrates the strengths of the constrained independent component analysis (cICA) extracting only the signals of interest (SOIs) with the advantage of ensemble empirical mode decomposition (EEMD) alleviating the mode mixing. The method, which is named EEMD-based cICA, not only enables gear fault feature extraction but also offers a new independent component analysis (ICA) mixing model with source noise and measured noise for the single-channel observation signal. The efficiency of the proposed method is tested on simulated as well as real-world vibration signals acquired from a multi-stage gearbox with a missing tooth and a chipped tooth, respectively." @default.
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- W2780496328 date "2017-12-31" @default.
- W2780496328 modified "2023-09-26" @default.
- W2780496328 title "EEMD-Based cICA method for single-channel signal separation and fault feature extraction of gearbox" @default.
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- W2780496328 doi "https://doi.org/10.21595/jve.2017.18115" @default.
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