Abstract
Recently, research concerning condition monitoring and fault diagnosis of electrical machines. The increasing importance of these energy conversion devices and their widespread use in uncountable applications has motivated significant research efforts. Various faults are occurring in the stator as well as in the rotor of 3-phase squirrel cage induction motor such as bearing fault, broken rotor bar fault, etc. This paper presents an analysis of fault occurring in the bearing of 3-phase squirrel cage induction motor by using artificial intelligence method. Bearings are critical components in induction motor. Bearing fault is the most common fault in induction motor. Motor bearing data with single point faults and generalised roughness faults are used to validate the effectiveness of the proposed method for fault diagnosis.
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