Prediction model of centrifugal fan performance based on BP neural network

Lei Zhang*, Chenxing Hu, Qian Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In view of the G4-73 type backward centrifugal fan widely used in power plant, training samples for orthogonal test is conducted. A Centrifugal fan performance parameters prediction model based on BP neural network is built. Through the contraction between the predictive value and samples, the accuracy of prediction model is verified. The maximum relative errors of total pressure and efficiency are respectively 0.974% and 0.3327% with the trained neural network to predict on each single test sample, which reaches the predetermined training accuracy, and can be used for fan performance prediction.

Original languageEnglish
Title of host publicationApplied Mechanics and Materials I
Pages2455-2458
Number of pages4
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2012 International Conference on Applied Mechanics and Materials, ICAMM 2012 - Sanya, China
Duration: 24 Nov 201225 Nov 2012

Publication series

NameApplied Mechanics and Materials
Volume275-277
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference2012 International Conference on Applied Mechanics and Materials, ICAMM 2012
Country/TerritoryChina
CitySanya
Period24/11/1225/11/12

Keywords

  • Centrifugal fan
  • Neural network
  • Structural parameter

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