Research on Stamping Spring-Back Prediction for Car Body Panel Based on BP Neural Network

Abstract:

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On the basis of orthogonal test analysis of variance, BP neural network is used to forecast quantitatively the stamping spring-back of front panel of a car body, namely the engine hood, under the conditions of different stamping parameters. Firstly, BP neural network prediction model is established and sample training is done in Matlab. Then, the spring-back prediction using BP neural network and the result of spring-back simulation using Dynaform is compared to verify the precision and stability of the prediction model. Lastly, modification is made to the BP neural network according to practical stamping parameters and an efficient BP neural network model is established. Using this model, stamping spring-back prediction for the front panel of a car body is made. The spring-back prediction could then be used for spring-back compensation in the mould design of the front panel.

Info:

Periodical:

Advanced Materials Research (Volumes 97-101)

Edited by:

Zhengyi Jiang and Chunliang Zhang

Pages:

250-254

DOI:

10.4028/www.scientific.net/AMR.97-101.250

Citation:

X. J. Zhou "Research on Stamping Spring-Back Prediction for Car Body Panel Based on BP Neural Network ", Advanced Materials Research, Vols. 97-101, pp. 250-254, 2010

Online since:

March 2010

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Price:

$35.00

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