Technologies for proactive maintenance by the hilbert huang transform (HHT) technique

Abstract

This work represents the new method of analyzing the vibration signals and fault diagnosis of the roller bearing. This non-destructive method is based on a new technique, Empirical Mode Decomposition (EMD) and Hilbert - Huang Transform (HHT) for non-stationary and non-linear time series analysis. First the vibration signals (time-domain signals) are decomposed into intrinsic oscillatory mode (IMF), providing a time-frequency distribution using the 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 obtained, based on the comparison of system properties 'before' and 'after' damage, with the premise that the system can be treated as linear in both sides. The data are obtained from the experiments conducted on a lab test set-up facility. The results show that it is a better promising method for the damage detection in the roller bearing, thus providing a viable signal processing tool for machine health monitoring.