According to the non-stationary characteristics of roller bearing fault vibration signals, a
roller bearing fault diagnosis method based on empirical mode decomposition (EMD) …

The ensemble empirical mode decomposition (EEMD) can overcome the mode mixing
problem of the empirical mode decomposition (EMD) and therefore provide more precise …

Based upon empirical mode decomposition (EMD) method and Hilbert spectrum, a method
for the fault diagnosis of roller bearings is proposed in this paper. The local Hilbert spectrum …

Feature extraction is one of the challenging problems in fault diagnosis, and it has a direct
bearing on the accuracy of fault diagnosis. Therefore, in this paper, a new method based on …

The main purpose of this paper is to propose a new fault feature extraction approach based
on empirical mode decomposition (EMD) method and autoregressive (AR) model for roller …

The fault signals of low-speed rolling elements bearing are non-stationary and non-linear,
and consequently it is difficult to extract the fault characteristics by the traditional time and …

Condition monitoring and fault diagnosis of rolling element bearings (REBs) are at present
very important to ensure the steadiness of industrial and domestic machinery. According to …

This paper proposes a fault diagnosis method for roller bearings based on the
decomposition of vibration signals using the empirical wavelet transform (EWT) with …

Since the vibration signals of roller bearings are non-linear and non-stationary, the fault
diagnosis of roller bearings is very difficult to determine. Characterized by the self-adaptive …

The condition monitoring and multi-fault diagnosis of rolling bearing is a very important
research content in the field of the rotating machinery health management. Most researches …