There have been extensive studies on vibration based condition monitoring, prognosis of rotating element bearings; and reviews of the
methods on how to identify bearing fault and predict the final failure reported widely in literature. The investigated bearings commonly
discussed in the literatures were run in moderate and high rotating speed, and damages were artificially introduced e.g. with artificial
crack or seeded defect. This paper deals with very low rotational-speed slewing bearing (1-4.5 rpm) without artificial fault. Two real
vibration data were utilized, namely data collected from lab slewing bearing subject to accelerated life test and from a sheet metal company.
Empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) were applied in both lab slewing
bearing data and real case data. Outer race fault (BPFO) and rolling element fault (BSF) frequencies of slewing bearing can be identified.
However, these fault frequencies could not be identified using fast Fourier transform (FFT).