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矩形盒拉深变压边力加载规律及预测 被引量:1

Loading Law of Variable Blank-holder Force and Its Prediction in Rectangular Box Deep Drawing
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摘要 目的解决板料拉深过程中出现拉裂、起皱、拉深不充分等缺陷的问题。方法利用专业分析板料成形的软件Dynaform,研究分析了非轴对称件矩形盒,在几种典型的变压边力下的拉深成形性能,获得了成形效果较好的加载模式,进而利用仿真软件Dynaform获取了样本数据。结果建立了矩形盒拉深成形变压边力网络模型并对其学习训练,最后对神经网络预测结果及仿真结果所得到的变压边力加载曲线进行多项式拟合,获取了最佳压边力控制曲线。结论在板料拉深过程中,通过控制压边力的大小,能够较好地发挥材料的流动性,改善制件的最终成形效果。 In order to eliminate the defects of cracking, wrinkling and inadequate stretching in the stretching process, the tensile forming properties of a rectangular box with a non-axial symmetric rectangular box under the typical variable blank holder force were studied by using the software Dynaform of the professional analysis of sheet metal forming. A more ideal loading mode of forming effect was obtained. Then the sample data was obtained by the simulation software Dynaform. A network model of variable blank holder force in rectangular box drawing forming was established and then studied and trained. Finally, the polynomial fitting of the curve of variable blank holder force was obtained by the neural network prediction results and the simulation results, and the optimal blank holder force control curve was obtained. In the stretching of sheet metal, control on the blank-holder force can better give play to the mobility of materials and improve the final shape effect.
出处 《精密成形工程》 2016年第4期33-37,共5页 Journal of Netshape Forming Engineering
关键词 矩形盒件 变压边力 拉深成形 神经网络 预测 rectangular box parts variable blank-holder force(VBHF) drawing forming neural networks prediction
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  • 1解晶,张丽香,张晶.模糊指数趋近律参数的二级倒立摆控制[J].电力学报,2012,27(1):44-46. 被引量:2
  • 2智会强,牛坤,田亮,杨增军.BP网络和RBF网络在函数逼近领域内的比较研究[J].科技通报,2005,21(2):193-197. 被引量:39
  • 3秦泗吉,马丽霞,李硕本.恒力拉伸压边装置的设计[J].模具工业,1997,23(4):22-23. 被引量:16
  • 4钟志华,李光耀. 薄板冲压成形过程的计算机仿真与应用. 北京:北京理工大学出版社,1998
  • 5Obermeyer E J. A review of recent advances in the application of blank-holder force towards improving the forming limits of sheet metal parts. Journal of material processing technology,1998,75:222~234
  • 6Manabe K,Soeda K. Adaptive control method of deep drawing using the variable blank holding force technique. Journal of the Japan Society for Technology of Plasticity,1992,33(375):423~428
  • 7Manabe K,Yang M,Yoshihare S. Artificial intelligence identification of process paramters and adaptive control system for deep-drawing process. Journal of Material Processing Technology,1998,80-81:421~426
  • 8闻新,周露,王丹力,著. 神经网络应用设计. 北京:科学出版社,2002
  • 9Li P L, Sang M H, Beom S K. Finite Element Analysis and Design in Stainless Steel Sheet Forming and Its Experimental Comparison [J]. Journal of Materials Processing Technology, 2001 ,110 (1) : 70- 77.
  • 10Luc P, Jean P P. Finite Element Simulation of Spring Back in Sheet Metal Forming[J]. Journal of Materials Processing Technology, 2002,125-126 (S) :785-791.

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