Parameter prediction in laser bending of aluminum alloy sheet |
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Authors: | Xuyue Wang Weixing Xu Hua Chen and Jinsong Wang |
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Affiliation: | (1) Key Laboratory for Precision and Non-traditional Machining Technology of the Ministry of Education, Dalian University of Technology, Dalian, 116024, China |
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Abstract: | 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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Translated from Optics and Precision Engineering, 2007, 15(6): 915–921 译自: 光学精密工程 |
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Keywords: | laser bending prompt heating aluminum alloy sheet parameter prediction |
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