| Autor: |
Siguerdidjane, Wassime, Khameneifar, Farbod, Gosselin, Frédérick P. |
| Rok vydání: |
2020 |
| Předmět: |
|
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1016/j.mfglet.2020.08.001 |
| Popis: |
Robust automation of the shot peen forming process demands a closed-loop feedback in which a suitable treatment pattern needs to be found in real-time for each treatment iteration. In this work, we present a method for finding the peen-forming patterns, based on a neural network (NN), which learns the nonlinear function that relates a given target shape (input) to its optimal peening pattern (output), from data generated by finite element simulations. The trained NN yields patterns with an average binary accuracy of 98.8\% with respect to the ground truth in microseconds. |
| Databáze: |
arXiv |
| Externí odkaz: |
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