Springback control in sheet metal bending by laser-assisted bending: Experimental analysis, empirical and neural network modelling

被引:54
|
作者
Gisario, A. [2 ]
Barletta, M. [1 ]
Conti, C. [1 ]
Guarino, S. [1 ]
机构
[1] Univ Roma Tor Vergata, Dipartimento Ingn Meccan, I-100133 Rome, Italy
[2] Univ Roma La Sapienza, Dipartimento Meccan & Aerospaziale, I-00184 Rome, Italy
关键词
Neural network; Modelling; Springback; Bending; Laser; ELEVATED-TEMPERATURES; RESIDUAL-STRESSES; ALUMINUM-ALLOYS; PREDICTION; COMPONENTS; MECHANISM; FORCE;
D O I
10.1016/j.optlaseng.2011.07.010
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
The present investigation deals with the control of springback phenomena in the bending process of aluminium sheets by hybrid forming process. Metal substrates were pre-bent to nominal shapes on a built-ad-hoc mould after being constrained on it. Then, they were post-treated by high power diode laser to prevent the deformation of the pre-bent sheets after the release of the constraints. The extent of springback phenomena were estimated by measuring the difference between the nominal bending angles and those achieved on the unconstrained substrates after laser post-treatments. Analytical models, aimed at predicting the springback by varying the setting of the operational parameters of the forming process, were developed. Neural network solutions were also proposed to improve the matching between experimental and numerical data, with the Multi-Layer Perceptrons trained by Back-Propagation algorithm being the fittest one. On this basis, a control modulus very useful to practitioners for automation and simulation purposes was built-on. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1372 / 1383
页数:12
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