BEARING FAULT DETECTION IN INDUCTION MOTORS USING VIBRATION ANALYSIS FOR CONDITION MONITORING
Keywords:
Electric Motors, Condition-Based Maintenance, Predictive Maintenance, Vibration Analysis, Induction Motors, Fault Detection, Preventive Maintenance, Bearing AnalysisAbstract
Electric motors are essential machinery used in various industries. However, these motors can fail
and breakdown due to various factors, such as oil usage, motor ventilation, layout, and electrical
considerations, causing critical levels of temperature and vibrations. Condition-based maintenance (CBM) or
predictive maintenance (PdM) is essential to monitor and maintain the motors and, therefore, prevent failures
or breakdowns. Vibration analysis techniques can be used in CBM, and this paper focuses on the vibration
analysis technique to detect faults in induction motors. The paper examines the sources of vibrations in
induction motors and highlights typical faults that can be detected, including imbalance, misalignment,
bearings, and electrical issues. The authors propose vibration monitoring as a preventive maintenance solution
to improve the performance and reliability of induction motors. The paper concludes with a case study on
bearing analysis, where the fault was caused by excessive stress on the bearing. The authors suggest
appropriate measures to prevent bearing faults and, therefore, prevent motor breakdowns.
