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2008年 第3卷 第3期

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《机械工程前沿（英文）》 >> 2008年 第3卷 第3期 doi: 10.1007/s11465-008-0046-x

Parameter prediction in laser bending of aluminum alloy sheet

Key Laboratory for Precision and Non-traditional Machining Technology of the Ministry of Education, Dalian University of Technology;

发布日期： 2008-09-05
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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.

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