Paper Title:
High-Pressure Water Spray Research Based on Neural Network
  Abstract

The spray cleaning method is important and universal in many industrial processes and other occasion. Because the size of the waterdrop is one of key factors for cleaning, this paper not only studied the relationship between the size of waterdrop and other influencing factors, but also researched the forecasted method for the size of waterdrop. In lab, by measuring the size of the waterdrop, jetted by one kind of nozzle, data were acquired and were used to train the Back Propagation Neural Network ( BPNN ). Through comparing those diameters, between measured in lab and calculated by BPNN after trained. It was acquired that the maximum errors was smaller than 1.62%, between the computed results and the factual measured ones. The experimental results showed that BPNN is an effective tool to predict the variation of the non-linear waterdrop diameter.

  Info
Periodical
Edited by
Honghua Tan
Pages
138-142
DOI
10.4028/www.scientific.net/AMM.29-32.138
Citation
R. Li, Z. M. Kou, "High-Pressure Water Spray Research Based on Neural Network", Applied Mechanics and Materials, Vols. 29-32, pp. 138-142, 2010
Online since
August 2010
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Price
$35.00
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