Bending Angle Prediction Model Based on BPNN-Spline in Air Bending Springback Process
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-02-27
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
In order to rapidly and accurately predict the springback bending angle in V-die air bending process, a springback bending angle prediction model on the combination of error back propagation neural network and spline function (BPNN-Spline) is presented in this study.
An orthogonal experimental sample set for training BPNN-Spline is obtained by finite element simulation.
Through the analysis of network structure, the BPNN-Spline black box function of bending angle prediction is established, and the advantage of BPNN-Spline is discussed in comparison with traditional BPNN.
The results show a close agreement with simulated and experimental results by application examples, which means that the BPNN-Spline model in this study has higher prediction accuracy and better applicable ability.
Therefore, it could be adopted in a numerical control bending machine system.
American Psychological Association (APA)
Guo, Zhefeng& Tang, Wencheng. 2017. Bending Angle Prediction Model Based on BPNN-Spline in Air Bending Springback Process. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1191966
Modern Language Association (MLA)
Guo, Zhefeng& Tang, Wencheng. Bending Angle Prediction Model Based on BPNN-Spline in Air Bending Springback Process. Mathematical Problems in Engineering No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1191966
American Medical Association (AMA)
Guo, Zhefeng& Tang, Wencheng. Bending Angle Prediction Model Based on BPNN-Spline in Air Bending Springback Process. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1191966
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1191966