Abstract
This paper analyses the important impact of laser texturing surface morphology on drawing forming. Based on the artificial neural network theory, the nonlinear mapping relations between the morphology parameters and the quality of drawing sheet was studied, the optimization model of laser texturing morphology parameters were established, and fixed on the optimization target, then the fitness function suitable for the genetic algorithm was determined, and the laser texturing morphology parameters were optimized. Taken BenDou for example, the multi-parameter numerical simulation was taken, and the morphology sharp parameters were obtained after the Genetic Algorithm. The results showed that parts with better formability, and noted that this method had better Optimizing guide.
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© 2009 Springer-Verlag Berlin Heidelberg
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Luo, Z., Fan, B., Guo, X., Wang, X., Li, J. (2009). Study on Optimization of the Laser Texturing Surface Morphology Parameters Based on ANN. In: Wang, H., Shen, Y., Huang, T., Zeng, Z. (eds) The Sixth International Symposium on Neural Networks (ISNN 2009). Advances in Intelligent and Soft Computing, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01216-7_63
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DOI: https://doi.org/10.1007/978-3-642-01216-7_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01215-0
Online ISBN: 978-3-642-01216-7
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