Predicting axial piston pump performance using neural networks Academic Article

abstract

• A neural network model for an axial piston pump (bent-axis design) is derived in this paper. The model uses data obtained from an experimental setup. The purpose of this ongoing study is the reduction of the power loss at high pressures. However, at the beginning, a study is being done to predict the behavior of the current design of the pump. The neural network model has a feedforward architecture and uses the Levenberg-Marquardt optimization technique in the training process. The model was able to predict the behavior of the pump accurately.

authors

• Karkoub, Mansour

published proceedings

• Mechanism and Machine Theory

author list (cited authors)

• Karkoub, M. A., Gad, O. E., & Rabie, M. G.

citation count

• 29

complete list of authors

• Karkoub, Mansour A||Gad, Osama E||Rabie, Mahmoud G

publication date

• November 1999

publisher

• Elsevier  Publisher

published in

• Mechanism and Machine Theory  Journal

keywords

• Neurosciences

Digital Object Identifier (DOI)

• 10.1016/s0094-114x(98)00086-x

start page

• 1211

end page

• 1226

volume

• 34

issue

• 8

URL

• http%3A%2F%2Fdx.doi.org%2F10.1016%2Fs0094-114x%2898%2900086-x