An Intelligent Fault Diagnosis of Induction Motors in an Arbitrary Noisy Environment

In this paper, an intelligent fault diagnosis system based on instantaneous power spectrum analysis is proposed. The instantaneous noise variations and sensor off-sets are considered to be one of the common factors that yield erroneous fault tracking in an online condition monitoring and fault diagnosis system. The developed system has the capability to detect bearing inner race defects at incipient stages with in an arbitrary noise conditions. An adaptive threshold has been designed to deal with line current noise ambiguities for decision-making on the existence of small fault signatures. The performance of the developed system has been analyzed theoretically and experimentally on a custom designed test rig under various loading conditions of the motor. © 2015, Springer Science+Business Media New York.