Title :
Incipient bearing fault diagnostics for inverter fed induction motor drive using ANFIS
Author :
Abu-Rub, H. ; Ahmed, Sabah M. ; Iqbal, A. ; Rahimian, M. ; Toliyat, H.A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ. at Qatar, Doha, Qatar
Abstract :
Incipient fault detection of electrical machine is a challenging task and requires intelligent diagnostic approach. Huge research effort is put to automate the fault diagnostic schemes. Among several causes of electrical machine failure the most frequent occurring fault is the mechanical bearing failure. Thus this paper present on-line diagnostic technique for incipient bearing failure in an inverter fed three-phase induction motor drive system. The adaptive neuro-fuzzy inference system is utilized for the diagnostic purpose. 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 :
fault diagnosis; induction motor drives; invertors; ANFIS; adaptive neuro-fuzzy inference system; electrical machine; incipient bearing fault diagnostics; inverter fed induction motor drive; mechanical bearing failure; Adaptive systems; Fault detection; Fault diagnosis; Friction; Induction motor drives; Torque; Incipient fault; Neuro-fuzzy inference; bearing fault; induction motor drive;
Conference_Titel :
Electrical Machines (ICEM), 2010 XIX International Conference on
Conference_Location :
Rome
Print_ISBN :
978-1-4244-4174-7
DOI :
10.1109/ICELMACH.2010.5608171