The development of an artificial neural network model to predict heating-line positions for plate forming in induction heating process
- Authors
- Nguyen, T.-T.; Yang, Y.-S.; Bae, K.-Y.
- Issue Date
- 2009
- Keywords
- Heating-line position; Induction heating; Neural network; Plate forming; Plate theory
- Citation
- Mechanics Based Design of Structures and Machines, v.37, no.2, pp 201 - 227
- Pages
- 27
- Indexed
- SCOPUS
- Journal Title
- Mechanics Based Design of Structures and Machines
- Volume
- 37
- Number
- 2
- Start Page
- 201
- End Page
- 227
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/27062
- DOI
- 10.1080/15397730902769356
- ISSN
- 1539-7734
1539-7742
- Abstract
- An artificial neural network model can help manufacturers determine the positions of induction heating lines and their heating parameters to form a desired shape of plate. The vertical displacements of a deformed plate are considered as the input parameters and the selected induction heating lines as output parameters to develop the model. The training patterns of neural network are obtained using an analytical solution that is derived from the plate theory to predict plate deformations in induction heating process. The plastic region in the analytical solution of the angular deformation of a steel plate is obtained from the thermal analysis of the plate with the heat input calculated from the electro-magnetic analysis of the induction heating process.
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Collections - 융합기술공과대학 > Division of Mechatronics Engineering > Journal Articles

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