کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
794160 | 1466777 | 2007 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Springback prediction for sheet metal forming based on GA-ANN technology
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Springback is a very important factor to influence the quality of sheet metal forming. Accurate prediction and controlling of springback is essential for the design of tools for sheet metal forming. In this paper, a technique based on artificial neural network (ANN) and genetic algorithm (GA) was proposed to solve the problem of springback. An improved genetic algorithm was used to optimize the weights of neural network. Based on production experiment, the prediction model of springback was developed by using the integrated neural network genetic algorithm. The results show that more accurate prediction of springback can be acquired with the GA-ANN model. It can be taken as a reference for sheet metal forming and tool design.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Materials Processing Technology - Volumes 187–188, 12 June 2007, Pages 227–231
Journal: Journal of Materials Processing Technology - Volumes 187–188, 12 June 2007, Pages 227–231
نویسندگان
Wenjuan Liu, Qiang Liu, Feng Ruan, Zhiyong Liang, Hongyang Qiu,