Predicting axial piston pump performance using neural networks

Mansour Karkoub, Osama E. Gad, Mahmoud G. Rabie

Research output: Contribution to journalArticle

27 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1211-1226
Number of pages16
JournalMechanism and Machine Theory
Volume34
Issue number8
DOIs
Publication statusPublished - Nov 1999
Externally publishedYes

    Fingerprint

ASJC Scopus subject areas

  • Bioengineering
  • Mechanics of Materials
  • Mechanical Engineering
  • Computer Science Applications

Cite this