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• W2848973885 abstract "Gearbox with hybrid distributed and localized faults usually generates coupled modulation vibration signal. It is hard to decompose the coupled signal for precise diagnosis. To solve this problem, a novel signal decomposition method is proposed on the basis of double-dictionary and split augmented Lagrangian shrinkage algorithm (SALSA). The dictionary possessing high similarity to fault features consists of steady modulation sub-dictionary and impact modulation sub-dictionary. The SALSA is improved by adding a hard threshold de-noising to obtain optimal sparse coefficients of steady modulation and impact modulation components. Key parameters including Lagrange multipliers (λs, λp), penalty factor μ of SALSA and hard threshold ε are studied to determine their optimal value ranges. Kinds of simulation signals show the effectiveness of the proposed method, and experimental tests on fixed-shaft gearbox and planetary gearbox further verify the reliability. Comparative analyses with methods respectively based on matching pursuit and tunable Q-factor wavelet transform indicate that the proposed method is superior to the other two methods in calculation efficiency and anti-noise performance, especially when these two kinds of modulation components are completely coupled in some resonance bands." @default.
• W2848973885 created "2018-07-19" @default.
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• W2848973885 date "2018-10-01" @default.
• W2848973885 modified "2023-10-16" @default.
• W2848973885 title "Double-dictionary signal decomposition method based on split augmented Lagrangian shrinkage algorithm and its application in gearbox hybrid faults diagnosis" @default.
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• W2848973885 doi "https://doi.org/10.1016/j.jsv.2018.06.064" @default.
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