Phase editing to enhance bearing fault detection in variable speed condition

The computation of the squared envelope spectrum (SES) on vibration data collected from a rotating machine is a common tool used to diagnose a defective bearing. To enhance the diagnosis, pre-processing methods have to be implemented, before the evaluation of the SES, to suppress vibrations from sources other than the bearings. Conventionally suppression of the spurious components is achieved by exploiting either their separation in the frequency domain or the contrast between deterministic signals and the random vibration components from a defective bearing. Recently the phase editing method (PE) was used to exploit another characteristic of the vibration signal to improve diagnosis in stationary speed conditions. PE caters to, and exploits the scenario
where vibrations from a defective bearing have small amplitude compared to vibrations from other components, eectively thresholding the amplitudes of the spectral components of a signal. In this paper the PE method is applied analytically and experimentally to a broader class of machinery, encompassing machines with varying speed conditions. It is demonstrated that the separation of the bearing component and masking components is equally eective in the non-stationary case.