DocumentCode
2564726
Title
Vibration signature analysis for detecting cavitation in centrifugal pumps using neural networks
Author
Nasiri, M.R. ; Mahjoob, M.J. ; Vahid-Alizadeh, H.
Author_Institution
NVA Res. Center, Univ. of Tehran, Tehran, Iran
fYear
2011
fDate
13-15 April 2011
Firstpage
632
Lastpage
635
Abstract
Vibration analysis is applied to detect cavitation in a centrifugal pump using a neural net system. The features extracted from vibration signals are used as inputs to the neural network. The output data of the system is set as 0,0.5 and 1, for normal condition, developed cavitation and fully developed cavitation, respectively. Experiments are also conducted to validate the developed model. The method provides an intelligent system to be used in condition monitoring of centrifugal pumps. Also the number of sensors and the best sensor positions are studied.
Keywords
cavitation; condition monitoring; feature extraction; mechanical engineering computing; neural nets; pumps; signal processing; vibrations; cavitation detection; centrifugal pumps; feature extraction; neural networks; sensor positions; vibration signals; vibration signature analysis; Irrigation; Noise; Noise measurement; cavitation; centrifugal pump; neural network; vibration signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronics (ICM), 2011 IEEE International Conference on
Conference_Location
Istanbul
Print_ISBN
978-1-61284-982-9
Type
conf
DOI
10.1109/ICMECH.2011.5971192
Filename
5971192
Link To Document