Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2017, Article ID 7834621, 11 pages
https://doi.org/10.1155/2017/7834621
Research Article

Bending Angle Prediction Model Based on BPNN-Spline in Air Bending Springback Process

Department of Mechanical Engineering, Southeast University, Nanjing 211189, China

Correspondence should be addressed to Wencheng Tang; nc.ude.ues@cwgnat

Received 16 October 2016; Revised 16 January 2017; Accepted 7 February 2017; Published 27 February 2017

Academic Editor: Marek Lefik

Copyright © 2017 Zhefeng Guo and Wencheng Tang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. D.-K. Leu, “Position deviation and springback in V-die bending process with asymmetric dies,” International Journal of Advanced Manufacturing Technology, vol. 79, no. 5–8, pp. 1095–1108, 2015. View at Publisher · View at Google Scholar · View at Scopus
  2. S. V. Mohammadi, M. Parsa, and M. Parsa, “Simplified springback prediction in Al/PP/Al sandwich air bending,” Journal of Sandwich Structures and Materials, vol. 17, no. 3, pp. 217–237, 2015. View at Publisher · View at Google Scholar · View at Scopus
  3. L. J. De Vin, “Expecting the unexpected, a must for accurate brakeforming,” Journal of Materials Processing Technology, vol. 117, no. 1-2, pp. 244–248, 2001. View at Publisher · View at Google Scholar · View at Scopus
  4. Y. Zong, P. Liu, B. Guo, and D. Shan, “Springback evaluation in hot v-bending of Ti-6Al-4V alloy sheets,” International Journal of Advanced Manufacturing Technology, vol. 76, no. 1–4, pp. 577–585, 2015. View at Publisher · View at Google Scholar · View at Scopus
  5. V. Vorkov, R. Aerens, D. Vandepitte, and J. R. Duflou, “Springback prediction of high-strength steels in large radius air bending using finite element modeling approach,” in Proceedings of the 11th International Conference on Technology of Plasticity (ICTP '14), pp. 1005–1010, Nagoya, Japan, October 2014. View at Publisher · View at Google Scholar · View at Scopus
  6. Z. M. Fu, W. Chen, X. L. Tian, and B. K. Hu, “Modeling and simulation for multiple-step incremental air-bending forming of sheet metal,” International Journal of Advanced Manufacturing Technology, vol. 72, no. 5–8, pp. 561–570, 2014. View at Publisher · View at Google Scholar · View at Scopus
  7. M. R. Jamli, A. K. Ariffin, and D. A. Wahab, “Incorporating feedforward neural network within finite element analysis for L-bending springback prediction,” Expert Systems with Applications, vol. 42, no. 5, pp. 2604–2614, 2015. View at Publisher · View at Google Scholar · View at Scopus
  8. M. Haddadzadeh, M. R. Razfar, and M. R. M. Mamaghani, “Novel approach to initial blank design in deep drawing using artificial neural network,” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 223, no. 10, pp. 1323–1330, 2009. View at Publisher · View at Google Scholar · View at Scopus
  9. H. Hasanzadehshooiili, A. Lakirouhani, and A. Šapalas, “Neural network prediction of buckling load of steel arch-shells,” Archives of Civil and Mechanical Engineering, vol. 12, no. 4, pp. 477–484, 2012. View at Publisher · View at Google Scholar · View at Scopus
  10. K. Hiramoto, “Control system design of mechanical systems with time varying mechanical and control parameters,” Journal of Advanced Mechanical Design, Systems, and Manufacturing, vol. 8, no. 3, pp. 1–14, 2014. View at Publisher · View at Google Scholar
  11. J. Xu, K. Yamada, K. Seikiya, R. Tanaka, and Y. Yamane, “Comparison of applying static and dynamic features for drill wear prediction,” Journal of Advanced Mechanical Design, Systems and Manufacturing, vol. 8, no. 4, p. JAMDSM0056, 2014. View at Publisher · View at Google Scholar · View at Scopus
  12. S. Kitayama, S. Huang, and K. Yamazaki, “Optimization of variable blank holder force trajectory for springback reduction via sequential approximate optimization with radial basis function network,” Structural and Multidisciplinary Optimization, vol. 47, no. 2, pp. 289–300, 2013. View at Publisher · View at Google Scholar · View at Scopus
  13. J. Srirat, S. Kitayama, and K. Yamazaki, “Simultaneous optimization of variable blank holder force trajectory and tools motion in deep drawing via sequential approximate optimization,” Journal of Advanced Mechanical Design, Systems and Manufacturing, vol. 6, no. 7, pp. 1081–1092, 2012. View at Publisher · View at Google Scholar · View at Scopus
  14. J.-H. Song, H. Huh, and S.-H. Kim, “Stress-based springback reduction of a channel shaped auto-body part with high-strength steel using response surface methodology,” Journal of Engineering Materials and Technology, Transactions of the ASME, vol. 129, no. 3, pp. 397–406, 2007. View at Publisher · View at Google Scholar · View at Scopus
  15. X.-Y. Guo, D. Li, Z. Wu, and Q.-H. Tian, “Application of response surface methodology in optimizaing the sulfation-roasting-leaching process of nickel laterite,” International Journal of Minerals, Metallurgy and Materials, vol. 19, no. 3, pp. 199–204, 2012. View at Publisher · View at Google Scholar · View at Scopus
  16. C. Shen, L. Wang, and Q. Li, “Optimization of injection molding process parameters using combination of artificial neural network and genetic algorithm method,” Journal of Materials Processing Technology, vol. 183, no. 2-3, pp. 412–418, 2007. View at Publisher · View at Google Scholar · View at Scopus
  17. Y. Rostamiyan, A. Seidanloo, H. Sohrabpoor, and R. Teimouri, “Experimental studies on ultrasonically assisted friction stir spot welding of AA6061,” Archives of Civil and Mechanical Engineering, vol. 15, no. 2, pp. 335–346, 2015. View at Publisher · View at Google Scholar · View at Scopus
  18. M. Winnicki, A. Małachowska, and A. Ambroziak, “Taguchi optimization of the thickness of a coating deposited by LPCS,” Archives of Civil and Mechanical Engineering, vol. 14, no. 4, pp. 561–568, 2014. View at Publisher · View at Google Scholar · View at Scopus
  19. Y. Tzeng, F. Chen, and C. Chen, “A hybrid approach for multi-objective design optimization of ball grid array gold wire bonding process,” Journal of Advanced Mechanical Design, Systems, and Manufacturing, vol. 9, no. 2, p. JAMDSM0021, 2015. View at Publisher · View at Google Scholar
  20. M. Piffl and E. Stadlober, “The depth-design: an efficient generation of high dimensional computer experiments,” Journal of Statistical Planning and Inference, vol. 164, pp. 10–26, 2015. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus