Abstract:
Induction motors have been responsible for
running mechanical systems in the industry for many
decades. Their diagnosis still remains a hot quest for the
researchers using various techniques. In this study, motor
current signature analysis (MCSA) technique has been used
to detect the faulty bearing installed in load machine (coupled to an induction motor). It has been seen that faulty
bearings installed in load machines do not directly alter airgap eccentricity of an induction motor. In fact, these bearing faults affect the resultant torque of an induction motor.
As modulating fault components show very low amplitude,
these are usually masked by noise. This paper is devoted
towards extracting features of faulty components efficiently
from stator current using continuous wavelet transform.
This methodology is assessed for detecting outer race
faults in bearings installed in load machines using MCSA.