Parameter prediction in laser bending of aluminum alloy sheet

被引:3
作者
Wang X. [1 ]
Xu W. [1 ]
Chen H. [1 ]
Wang J. [1 ]
机构
[1] Key Laboratory for Precision and Non-traditional Machining Technology, Ministry of Education, Dalian University of Technology
来源
Frontiers of Mechanical Engineering in China | 2008年 / 3卷 / 3期
基金
中国国家自然科学基金;
关键词
Aluminum alloy sheet; Laser bending; Parameter prediction; Prompt heating;
D O I
10.1007/s11465-008-0046-x
中图分类号
学科分类号
摘要
Based on the basic platform of BP neural networks, a BP network model is established to predict the bending angle in the laser bending process of an aluminum alloy sheet (1-2 mm in thickness) and to optimize laser bending parameters for bending control. The sample experimental data is used to train the BP network. The nonlinear regularities of sample data are fitted through the trained BP network; the predicted results include laser bending angles and parameters. Experimental results indicate that the prediction allowance is controlled less than 5%-8% and can provide a theoretical and experimental basis for industry purpose. © 2008 Higher Education Press.
引用
收藏
页码:293 / 298
页数:5
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