Hilbert-Huang Transform and Marginal Spectrum for Detection of Bearing Localized Defects

This work presents the application of a new signal processing technique, the Hilbert-Huang transform and its marginal spectrum, in analysis of vibration signals and faults diagnosis of roller bearing. The empirical mode decomposition (EMD), Hilbert-Huang transform (HHT) and marginal spectrum is introduced. Firstly, the vibration signals are separated into several intrinsic mode functions (IMFs) using EMD. Then the marginal spectrum of each IMF can be obtained. According to the marginal spectrum, the localized fault in a roller bearing can be detected and faults patterns can be identified. The results show that the proposed method may provide not only an increase in the spectral resolution but also reliability for the faults diagnosis of roller bearing

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