Speed variant motor fault diagnosis applying significant frequency bands

Abstract

The need for proper diagnosis and prediction of motor faults is vital for reliable and smooth operation of industrial sites. This however, is expensive, complex and hard to meet the standard required of reliable protection system. The diagnosis problems are more serious in speed variant motors because of change of placements and configurations of faulty patterns. In this paper, using Motor current signature analysis, a simple and effective method is proposed in pattern reorganization. In this strategy, the possibility of the presence of a fault symptom, in well known frequency zones and, expected portion of detectable faults in significant frequency zones is applied to measure and possibility rank the seriousness of faulty events in electrical machines.