کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1636625 1516983 2013 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Springback prediction for incremental sheet forming based on FEM-PSONN technology
موضوعات مرتبط
مهندسی و علوم پایه مهندسی مواد فلزات و آلیاژها
پیش نمایش صفحه اول مقاله
Springback prediction for incremental sheet forming based on FEM-PSONN technology
چکیده انگلیسی
In the incremental sheet forming (ISF) process, springback is a very important factor that affects the quality of parts. Predicting and controlling springback accurately is essential for the design of the toolpath for ISF. A three-dimensional elasto-plastic finite element model (FEM) was developed to simulate the process and the simulated results were compared with those from the experiment. The springback angle was found to be in accordance with the experimental result, proving the FEM to be effective. A coupled artificial neural networks (ANN) and finite element method technique was developed to simulate and predict springback responses to changes in the processing parameters. A particle swarm optimization (PSO) algorithm was used to optimize the weights and thresholds of the neural network model. The neural network was trained using available FEM simulation data. The results showed that a more accurate prediction of springback can be acquired using the FEM-PSONN model.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Transactions of Nonferrous Metals Society of China - Volume 23, Issue 4, April 2013, Pages 1061-1071
نویسندگان
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