@inproceedings{dabbb7632a924352af919a048205fa22,
title = "Incipient bearing fault detection for three-phase brushless DC motor drive using ANFIS",
abstract = "Incipient fault detection of electrical machine is a major task and requires intelligent diagnostic approach. Extensive research has been performed in the field of automation of fault diagnostic schemes. Among several causes of electrical machine failure the most frequent occurring fault is the mechanical bearing failure. Thus, this paper presents diagnostic technique for incipient bearing failure in a three-phase Brushless DC (BLDC) motor drive system. The Adaptive Neuro-Fuzzy Inference System is utilized for the diagnostic purpose. The proposed approach offers accurate estimate of the bearing conditions with minimal effort. The proposed technique is verified using simulation approach. The simulation is done using Matlab/Simulink and the complete model is presented in the paper.",
keywords = "BLDC drive, Incipient fault, Neuro-Fuzzy Inference, bearing fault",
author = "Haitham Abu-Rub and {Moin Ahmed}, Sk and Atif Iqbal and Toliyat, {Hamid A.} and Rahimian, {Mina M.}",
year = "2011",
doi = "10.1109/DEMPED.2011.6063688",
language = "English",
isbn = "9781424493036",
series = "SDEMPED 2011 - 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives",
pages = "620--625",
booktitle = "SDEMPED 2011 - 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives",
note = "8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2011 ; Conference date: 05-09-2011 Through 08-09-2011",
}