Continuous condition assessment of induction motors is very important due to
its potential to reduce down-time and manpower needed in industry. Rolling element
bearing faults result in more than 40% of all induction motor failures. Vibration
analysis has been utilized to detect bearing faults for years. However, vibration
sensors and expert vibration interpretation are expensive. This limitation prevents
widespread monitoring of continuous bearing conditions in induction motors, which
provides better performance compared to periodic monitoring, a typical practice for
motor bearing maintenance in industry. A strong motivation exists for finding a costeffective
approach for the detection of bearing faults. Motor terminal signals have
attracted much attention. However, not many papers in the literature address this
issue as it relates to bearing faults, because of the difficulties in effective detection.
In this research, an incipient bearing fault detection method for induction motors
is proposed based on the analysis of motor terminal voltages and currents. The basic
idea of this method is to detect changes in amplitude modulation between the spatial
harmonics caused by bearing faults and the supply fundamental frequency. This
amplitude modulation relationship can be isolated using the phase coupling property.
An Amplitude Modulation Detector (AMD), developed from higher order spectrum
estimation, correctly captures the phase coupling and isolates these modulation relationships.
In this research, in-situ bearing damage experiments are conducted so that the
accelerated life span of the bearing can be recorded and investigated. Experimental
results shown in this dissertation are based on different power supplies, load levels, VSI
control schemes, and motor operating conditions. Taking the mechanical vibration
indicator as a reference for fault detection, the proposed method is demonstrated to
be effective in detecting incipient bearing faults in induction motors. If motors are
operating at near steady state conditions, then experimental results show that the
bearing fault detection rate of the proposed approach is 100%, while no false alarms
are recorded
