Condition monitoring and fault diagnosis of induction motor using neuro fuzzy logic - Hussein Adel Taha Hussein; Mohamed Ahmed Moustafa Hassan; Mohammed Elsayed Ammar (Cairo : Hussein Adel Taha Hussein, 2014)
The Induction machine is one of mostly common machine. It is almost used for all industrial applications, wind energy generation and recently it has been proposed for applications of hybrid electrical vehicle and electrical air craft. Fault monitoring and control becomes high priority for induction machine. This thesis discusses the fault diagnosis and monitoring of the induction motor, starting with the machine different faults and the different algorithms to detect these faults (intelligent control, parameter estimation{u2026}). The scope of this research is the fault with high occurrence percentage, which is stator turns faults. It is built on objects of: a) Three phase induction motor modeling in both the symmetric healthy and asymmetric faulty cases using of dq frames instead of ABC. b) An algorithm of on - line fault detection based on the motor fault response and motor electrical parameters change. c) The efficient design of an adaptive neuro fuzzy system
Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electrical Power and Machines
Issued also as CD
Keywords: ANFIS; Dq modeling; Induction motor