权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Development of an Intelligent System for Sheet Metal Bending

钣金折弯智能系统的开发

基本信息

批准号：
03555026
负责人：
SHIMA Susumu
金额：
$ 8.26万
依托单位：
KYOTO UNIVERSITY
依托单位国家：
日本
项目类别：
Grant-in-Aid for Developmental Scientific Research (B)
财政年份：
1991
资助国家：
日本
起止时间：
1991 至 1992
项目状态：
已结题

项目摘要

This project is to develop an intelligent metal forming system, in particular a common sheet metal bending, that performs flexibility in production and high accuracy incorporating feed forward control. By using a newly developed bending tool set which is suitable for displacement control, deformation of sheet metal is measured on-line ; the material properties was estimated by the measured data and combining with high accuracy of the tool displacement was performed. Further, a neural network was incorporated in the control system for further improvement of accuracy.(1) Instead of conventional V-angled bending tool, the newly developed tools of circular or elliptical shape was used to bend sheet metals on a prototype bending machine. It was thus confirmed that flexibility was improved and the accuracy was also improved by one fold. This is due to the learning control system.(2) In the above tool est, the contact point between the workpiece and the tool shifts according to the tool displacement. An intelligent sensor that measures the forces, both normal and tangential directions, was developed. The contact point and thus bend angle can be measured.(3) A neural network, which describes complicated phenomena was incorporated in the system to develop a control model with high accuracy. The material properties estimated by the deformation model was input into the neural network and binding condition was thus determined. It was thus concluded that combination of plasticity model and neuro-model has its potential of an efficient control model with high accuracy.

该项目旨在开发一种智能金属成型系统，特别是常见的钣金折弯系统，该系统具有生产灵活性和结合前馈控制的高精度。采用新开发的适合位移控制的折弯工装组，在线测量板材变形；通过测量数据来估计材料特性，并结合高精度的工具位移来进行。此外，在控制系统中加入了神经网络，进一步提高了精度。(1)用新开发的圆形或椭圆形工具代替传统的V形折弯工具，在原型折弯机上弯曲金属板材。由此证实，灵活性提高了，并且精度也提高了一倍。这是由于学习控制系统的原因。 (2) 在上述刀具测试中，工件和刀具之间的接触点根据刀具位移而移动。开发了一种可以测量法向和切向方向的力的智能传感器。可以测量接触点，从而测量弯曲角度。(3)系统中引入了描述复杂现象的神经网络，以开发高精度的控制模型。将变形模型估计的材料特性输入神经网络，从而确定结合条件。由此得出结论，可塑性模型和神经模型的结合具有成为高精度、高效控制模型的潜力。