Paper Title:
The Prediction of Shot Peening’s Surface Roughness with Premixed Water Jet Based on Neural Network
  Abstract

Shot peening’s surface roughness is an important factor affecting the effect of shot-peening. The paper selects blasting pressure, scanning speed and target distance as affecting factors in the process parameters, the shot penning test which aims at 2A11 aluminum alloy materials through applying the premixed water jet, according to test data, the paper establishes mathematical model of shot peening’s surface roughness applying neural network, and applies this model to predict shot peening’s surface roughness. The results show that the training average error of this model is small, the predicted effect is good, it can meet the requirements of shot peening’s surface roughness prediction accuracy in the industrial production, it has greater practical value.

  Info
Periodical
Edited by
Dunwen Zuo, Hun Guo, Hongli Xu, Chun Su, Chunjie Liu and Weidong Jin
Pages
172-175
DOI
10.4028/www.scientific.net/AMR.136.172
Citation
R. H. Wang, C. Wang, X. M. Zhang, "The Prediction of Shot Peening’s Surface Roughness with Premixed Water Jet Based on Neural Network", Advanced Materials Research, Vol. 136, pp. 172-175, 2010
Online since
October 2010
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Price
$32.00
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