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

Hashmia Sh. Dakheel, Zainab B. Abdulla, Helen Jassim Jawad


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.

Full Text:


DOI: http://doi.org/10.11591/ijape.v8.i2.pp173-185


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

International Journal of Applied Power Engineering (IJAPE)
p-ISSN 2252-8792, e-ISSN 2722-2624

Web Analytics Made Easy - StatCounter IJAPE Visitors