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• W3206148766 abstract "Time-frequency (TF) features of nonstationary vibrations are indicative of the health condition of rotating machinery and, are also pivotal in analyzing acoustic signals obtained from processes such as bat echo-location. However, the TF features in these nonstationary vibration and acoustic signals are often submerged by strong background noise. This article proposes using the refined matching linear chirplet transform (RMLCT) to enhance the TF features, where the chirp rates are adaptively determined by spectral kurtosis and only the interesting time-frequency representations (TFRs) are retained. With selected chirp rates, a novel transformation kernel is developed, enabling the proposed method to simultaneously process nonstationary multicomponent signals. Moreover, the angle refinement strategy is proposed to improve the noise-handling capability of the proposed method. The signal reconstruction of the RMLCT is also analyzed, demonstrating that signal components of interest can be accurately reconstructed. Numerical and experimental analyses validate the effectiveness of the proposed RMLCT." @default.
• W3206148766 created "2021-10-25" @default.
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• W3206148766 date "2022-01-01" @default.
• W3206148766 modified "2023-09-25" @default.
• W3206148766 title "Refined matching linear chirplet transform for exhibiting time-frequency features of nonstationary vibration and acoustic signals" @default.
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• W3206148766 doi "https://doi.org/10.1016/j.measurement.2021.110298" @default.
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