A review of intelligent methods for condition monitoring and fault diagnosis of stator and rotor faults of induction machines

Nowadays, induction motor (IM) is extensively used in industry, including mechanical and electrical applications. However, three main types of IM faults have been discussed the literature, bearing, stator, rotor. Importantly, stator rotor represent approximately 50%. Traditional condition monitoring (CM) fault diagnosis (FD) methods require a high processing cost much experience knowledge. To tackle this challenge, artificial intelligent (AI) based CM FD techniques are developed. there many review research papers for machine learning rolling elements bearings literature. Whereas lack not both FD. Thus, proposed study's contribution reviewing IM, especially rotor, on AI methods. The paper also provides discussions challenges possible future works.