Transactions of Materials and Heat Treatment

Title：Simulation and prediction of crosssection quality for precut blanking based on BP neural network

Authors： Zhang Liang

Unit： Department of Electrical and Mechanical Engineering Jiangyin Polytechnic College

KeyWords： precut blanking blanking crosssection quality BP neural network orthogonal test finite element simulation

ClassificationCode：TG385

year,vol(issue):pagenumber：2018,43(12):175-179

Abstract：

For stamping part of automobile, the precut blanking process of QSTE460 sheet metal was simulated by finite element software DEFORM2D, and the experimental value of blanking crosssection quality was 0.557 mm by the blanking experiment. Then, the relative error between simulated value and experimental value is 9.72% which verifies the correctness of finite element simulation, and the crosssection quality of precut blanking was simulated and predicted by the precut blanking orthogonal test and BP neural network. Furthermore, the three layer BP neural network structure of 5-12-1 was established by taking the precut depth, blanking clearance, blanking speed, precut blanking clearance and edge radius of punch as the input layer and taking the length of bright band as the output layer. After training and testing of BP neural network, the results show that the maximum relative error between prediction value of BP neural network and simulation value of finite element is 1.44%, which provides a more reliable prediction method for the prediction of blanking crosssection quality.

Funds：

作者简介：张良（1973-），男，硕士，副教授 Email：zlthzl@hotmail.com

Reference：

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