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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.

本计画旨在开发一种智慧型金属成形系统，特别是一种普通的金属板料折弯系统，其生产弹性与高精度皆可结合前馈控制。采用新开发的适合位移控制的折弯工装，在线测量板材变形量，根据测量数据估计材料性能，并结合高精度的工装位移进行加工。此外，神经网络被纳入控制系统，以进一步提高精度。(1)用新研制的圆形或椭圆形弯曲工具代替传统的V形弯曲工具，在原型弯曲机上对金属板材进行了弯曲。由此证实，灵活性得到了提高，准确性也提高了一倍。这是由于学习控制系统。(2)在上述工具测试中，工件和工具之间的接触点根据工具位移而移位。研制了一种能同时测量法向力和切向力的智能传感器。可以测量接触点和弯曲角度。(3)一个神经网络，它描述了复杂的现象被纳入系统开发的控制模型具有高精度。将变形模型估计的材料性能输入神经网络，确定约束条件。因此，塑性模型和神经元模型相结合，有可能成为一种高精度的有效控制模型。