Development of a neural network model to predict distortion during the metal forming process by line heating
In order to achieve automation of the plate forming process by line heating, it is necessary to know in advance the deformation to be obtained under specific heating conditions. Currently, different methods exist to predict deformation, but these are limited to specific applications and most of them...
Enregistré dans:
| Auteur principal: | |
|---|---|
| Autres auteurs: | , , , |
| Format: | article |
| Langue: | anglais |
| Publié: |
2013
|
| Sujets: | |
| Accès en ligne: | http://ridda2.utp.ac.pa/handle/123456789/2864 |
| Tags: |
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires: Development of a neural network model to predict distortion during the metal forming process by line heating
- A numerical study of parameters governing an inherent deformation database of plates formed by line heating
- Analysis and Prediction of Heat Induced Deformation Produced By the Line Heating Process Using the Finite Element Method
- Numerical study of inherent deformation produced in thick plates through bending by line heating
- Influential factors affecting inherent deformation during plate forming by line hating (Report 1) - the effect of plate size and edge effect
- Numerical analysis of the straightening process of thin plate structures by elastic FEM based on the inherent strain method
- Coordinated control for vehicles coopearative maneuvers using distributed model predictive control