Title :
Using rough sets techniques as a fault diagnosis classifier for induction motors
Author :
Bonaldi, E.L. ; Da Silva, L. E Borges ; Lambert-Torres, C. ; Oliveira, L.E.L. ; Assunco, F.O.
Author_Institution :
Electron. Eng. Departament, Escola Fed. de Engenharia de Itajuba, Brazil
Abstract :
This paper describes the ongoing research on rough sets based classifier applied to induction motors fault diagnosis through motor current signature analysis (MCSA). The results of mechanical failures detection and how a rough sets based classifier is used as a monitoring system using current signature analysis in predictive maintenance are described in this paper.
Keywords :
electric current measurement; fault diagnosis; induction motors; rough set theory; signal processing; spectral analysis; fault diagnosis classifier; induction motors; induction motors fault diagnosis; mechanical failures detection; monitoring system; motor current signature analysis; predictive maintenance; rough sets based classifier; rough sets techniques; spectral analysis; Air gaps; Condition monitoring; Fault detection; Fault diagnosis; Frequency; Humans; Induction motors; Predictive maintenance; Rough sets; Stators;
Conference_Titel :
IECON 02 [Industrial Electronics Society, IEEE 2002 28th Annual Conference of the]
Print_ISBN :
0-7803-7474-6
DOI :
10.1109/IECON.2002.1182941
