Motor Current Signature Analysis for Detecting Local Defects on Rolling-Element Bearings of Induction Motors

Motor current signature analysis is a useful method for detecting incipient faults in induction motors (IMs). However, the harmonic components introduced in the IM current by the local defects of the rolling-element bearing are usually too weak to be detected using common signal processing techniques such as the fast Fourier transform. In this paper, a three-phase IM is considered and local defects are created on its inner ring, outer ring, ball and cage, in turn. Then a proper test rig is prepared to sample and record the stator current at no load, full load and different temperatures under the healthy and defective bearing conditions. The recorded current signals are then decomposed into their intrinsic mode functions (IMFs) using the empirical mode decomposition algorithm. By applying Hilbert transform to the attained IMFs, it becomes clear that the fault-related harmonics are easily detectable in the first IMF. The study reveals that this method enables to detect the bearing local defects on its different parts with different severities under variable operating loads and temperatures.

Automated summary

Motor current signature analysis is a useful method for detecting incipient faults in induction motors. However, the harmonic components introduced by local defects in the rolling-element bearing are usually too weak to be detected using common signal processing techniques such as the fast Fourier transform.