Arabaci, HayriBilgin, OsmanUrkmez, Abdullah2020-03-262020-03-262007978-1-4244-0890-0https://hdl.handle.net/20.500.12395/21657Joint Conference on Electromotion/IEEE Aegean Conference on Electrical Machines and Power Electronics/ -- SEP 10-12, 2007 -- Bodrum, TURKEYIn this study, rotor faults detection in submersible induction motors which is used at deep well submersible pumps is presented by analyzing stator current. In some production squirrel cage rotor bars are welded to end rings by argon welding. While the welding sometimes some bars are not connected to end rings ore bad connection have been occurred. This affects the motor performance. For not preventing the production speed motor tests should be made quickly. In this study practical results are taken from POLMOT factory which produce submersible induction motors. When the motor construction is finished its robustness is tested with no load test. Their stator current time frequency domain is made and its current spectrum is investigated. According to current spectrum analysis its fault and robustness is determined. For classification Artificial Neural Network (ANN) is used. A decision mechanism that uses ANN result matrixes is occurred to detect faulted rotors.eninfo:eu-repo/semantics/closedAccessConference Object222225N/AWOS:000256943100037N/A