Title :
An automated system for incipient fault detection and diagnosis in induction motors based on MCSA
Author :
Da Silva Gazzana, Daniel ; Pereira, Luís Alberto ; Fernandes, Dênis
Author_Institution :
Dept. of Electr. Eng., Fed. Univ. of Rio Grande do Sul, Porto Alegre, Brazil
Abstract :
The paper describes a system for automated detection of incipient faults in induction machines. The system is based on the Motor Current Signature Analysis method (MCSA) and aimed to be applied in a thermal electric power plant in south Brazil. First, the mechanism of fault evolution is introduced and clarified regarding the most common induction motor faults: stator winding short-circuits, broken and cracked rotor bars and eccentricity faults. The influence of the load condition on the fault indicator is discussed based on practical cases, obtained through fault simulations using a prototype. The main theoretical and conceptual aspects of the developed system are presented, including the signal acquisition and conditioning as well the database which stores the motor signals acquired over a time period. Some results from the practical use of the system are shown to illustrate the system capabilities.
Keywords :
fault diagnosis; induction motors; short-circuit currents; thermal power stations; Brazil; cracked rotor bars; eccentricity faults; fault diagnosis; fault evolution mechanism; fault simulations; incipient fault detection automated system; induction motors; motor current signature analysis method; signal acquisition; stator winding short-circuits; thermal electric power plant; Bars; Databases; Electrical fault detection; Fault detection; Fault diagnosis; Induction machines; Induction motors; Rotors; Stator windings; Virtual prototyping;
Conference_Titel :
Industrial Technology (ICIT), 2010 IEEE International Conference on
Conference_Location :
Vi a del Mar
Print_ISBN :
978-1-4244-5695-6
Electronic_ISBN :
978-1-4244-5696-3
DOI :
10.1109/ICIT.2010.5472613