DocumentCode :
2825770
Title :
Hybrid method for the diagnosis of electrical rotary machines by vibration signals
Author :
Sanz, Fredy A. ; Ramirez, Juan M. ; Correa, Rosa E.
Author_Institution :
Dept. of Electr. Eng., CINVESTAV - GDL, Zapopan, Mexico
fYear :
2010
fDate :
26-28 Sept. 2010
Firstpage :
1
Lastpage :
6
Abstract :
The vibration study in rotational electrical machines is a research topic that involves mathematical modeling, model identification, and signal analysis, among others. The failures in motors and generators modify the vibration signals. In this paper, the use of Adaptive Networks Based on Fuzzy Inference System (ANFIS) is proposed for rotary electrical machines´ diagnosis, because it is able to achieve consistent approximations of machines´ behavior when facing a faulty condition or functioning normally. Results using actual measurements are valuable and give higher expectations for the future.
Keywords :
electric generators; electric machines; electric motors; ANFIS; adaptive networks; electrical rotary machines diagnosis; fuzzy inference system; generators; mathematical modeling; model identification; motors; rotational electrical machines; signal analysis; vibration signals; Adaptive systems; Bars; Induction motors; Time frequency analysis; Vibration measurement; Vibrations; ANFIS; Electrical machines; Faults; Vibrations; Wavelet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
North American Power Symposium (NAPS), 2010
Conference_Location :
Arlington, TX
Print_ISBN :
978-1-4244-8046-3
Type :
conf
DOI :
10.1109/NAPS.2010.5619959
Filename :
5619959
Link To Document :
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