METHOD FOR ROLLING BEARING FAULT DETECTION BASED ON ENHANCING STATISTICAL ASYMMETRY

A method for digital processing of vibration signals from rolling bearings in rotating machines is presented, allowing subsequent fault detection with high reliability. A linear, adaptive filter is applied to the acquired vibration signal and iteratively tuned to increase the statistical asymmetry of its output. In this process, the filter removes phase- and amplitude distortion from underlying fault impulses. Furthermore, suppression of sinusoidal disturbances is simultaneously achieved with high robustness to measurement noise. The result is a processed signal from which rolling bearing defects are more easily detected.