Hilbert-Huang transform and marginal spectrum for detection and diagnosis of localized defects in roller bearings

Abstract

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 fault diagnosis of roller bearings. The empirical mode decomposition (EMD), Hilbert-Huang transform (HHT) and marginal spectrum are introduced. First, the vibration signals are separated into several intrinsic mode functions (IMFs) by 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 fault patterns can be identified. The experimental results show that the proposed method may provide not only an increase in the spectral resolution but also reliability for the fault detection and diagnosis of roller bearings.