Vibration-based cavitation detection in centrifugal pumps
Ali Hajnayeb 1  
,  
Razieh Azizi 1  
,  
Afshin Ghanbarzadeh 1  
,  
 
 
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Shahid Chamran University of Ahvaz
CORRESPONDING AUTHOR
Ali Hajnayeb   

Shahid Chamran University of Ahvaz, Daneshgah square, 6135743337 Ahvaz, Iran
Publication date: 2017-09-18
Submission date: 2017-06-30
Final revision date: 2017-08-16
Acceptance date: 2017-08-18
 
Diagnostyka 2017;18(3):77–83
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ABSTRACT
Cavitation is a common cause of failure in centrifugal pumps. Because of interaction of several mechanical parts and fluid, the vibration signal of a centrifugal pump is complicated. In this paper, the vibrations of a transparent-casing centrifugal pump are studied. Three states are studied experimentally: no cavitation, limited cavitation and developed cavitation. Each case was also confirmed by visually inspecting the cavitation bubbles. The vibrations of the pump was acquired by using an accelerometer that was attached to the casing. Discrete wavelet transform (DWT) analysis and empirical mode decomposition (EMD) are used to extract classification features from the acquired signals. Using these features, an artificial neural network (ANN) successfully diagnosed the cavitation condition of the pump. Finally, EEMD is also implemented. The results showed the success of EMD and DWT in cavitation diagnosis. The output of EEMD does not show significant change comparing to EMD.
eISSN:2449-5220
ISSN:1641-6414