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International Journal of Rotating Machinery
Volume 4, Issue 1, Pages 49-59

Fault Diagnostic Method for Pump Running Conditions Based on Process Modeling and Neural Network

1School of Informatics and Sciences, Nagoya University, Furo-Cho, Chikusa-Ku, Nagoya 464-01, Japan
2Institute of Hydraulic Turbomachinery and Fluid Mechanics, Technical University of Berlin, Germany

Received 6 September 1996; Revised 15 November 1996

Copyright © 1998 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper proposes a fault diagnostic method for pump running conditions. The method is a combination of a process modeling and a classification procedure. The pump head and hydraulic losses in the pipe system are modeled by two equations. The values of the coefficients in the equations are determined from measurable output variables of the pump. Since the pump running conditions affect the coefficient values, they are detected by classifying those values. A multi-layer neural network is employed for the classification. Three running conditions of a drainage pump are clearly detected by this method. The accuracy of detection is improved by increasing the hidden layers and their units in the neural network.