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