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- W2386836684 abstract "A fault feature extraction method of rolling bearing based on ensemble empirical mode decomposition (EEMD) and scale-transformation stochastic resonance(STSR) is proposed.Firstly,the vibration signal with noise is adaptively anti-aliasing decomposed by EEMD to conduct intrinsic mode function(IMF) of different frequency bands.Then making the IMFs as the input of bi-stable system,the low frequency fault features signal is extracted by the step-changed numberical algorithm and the adjustment of the bi-stable system parameters. Finally,slice bi-spectrum is adopted to postprocess the output of the bi-stable system.Simulation analysis is performed to prove the characteristics of STSR,the analysis on measured signal of the rolling bearing in strong background noise shows that the approach can extract the weak fault features of rolling bearing with the full use of Gaussian white noise successfully." @default.
- W2386836684 created "2016-06-24" @default.
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- W2386836684 date "2013-01-01" @default.
- W2386836684 modified "2023-09-24" @default.
- W2386836684 title "Bearing Fault Diagnosis Based on EEMD and STSR" @default.
- W2386836684 hasPublicationYear "2013" @default.
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