Performance degradation assessment of rolling element bearings is vital for the reliable and cost-efficient operation and maintenance of rotating machines, especially for the implementation of condition-based maintenance (CBM). For robust degradation assessment of rolling element bearings, uncertainties such as those induced from usage variations or sensor errors must be taken into account. Thi...

Rolling bearings are widely used in rotating equipment. Detection of bearing faults is of great importance to guarantee safe operation of mechanical systems. Acoustic emission (AE), as one of the bearing monitoring technologies, is sensitive to weak signals and performs well in detecting incipient faults. Therefore, AE is widely used in monitoring the operating status of rolling bearing. This p...

A defect-free rolling element bearing has a varying stiffness. The variation of stiffness depends on number of rolling elements, their configuration and cage frequency. The time-varying characteristics of the stiffness results in a parametric excitation. This may lead to instability which is manifested as high vibration levels. An FEM simulation is performed to evaluate stiffness in each config...

In this paper the wavelet packet transform is used for processing of rolling element bearing fault signals. The effectiveness of the envelope analysis technique is combined with the flexibility of the wavelet packet transform, helping in the minimization of interventions by the end user. According to the proposed method, a time-frequency decomposition of a vibration signal is provided and the c...

Envelope Detection (ED) is traditionally always used with Fast Fourier Transform (FFT) to identify the rolling element bearing faults. The inability of FFT to detect non-stationary signals makes Wavelet Analysis (WA) an alternative for machinery fault diagnosis as WA can detect both stationary and non-stationery signals. A comparative study of ED with FFT and WA techniques for bearing fault dia...