Faults detection and diagnoses of permanent magnet synchronous motor based on neuro-fuzzy network

Hashmia Sh. Dakheel (Electromechanical Department, University of Technology, Iraq)
Zainab B. Abdulla (Electromechanical Department, University of Technology, Iraq)
Helen Jassim Jawad (Electromechanical Department, University of Technology, Iraq)

International Journal of Applied Power Engineering (IJAPE)
Vol 8, No 2: August 2019

Faults in electrical machine are very important in order to improve the machine expensive maintenance, efficiency, life time, and reliability at real time, therefore this study deals with Simulink model response for healthy and neuro-fuzzy network (ANFIS), this intelligent technique consist of two parts, the first part include electrical and demagnetization faults while another part deals with mechanical faults. Simulation results obtain record activation, high performance, and efficiency of this network.