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

Abstract:

Article Preview

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 et al., "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

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.