Vibration signature analysis for detecting cavitation in centrifugal pumps using neural networks

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.