针对传统板形预测模型的固有缺陷,研究建立了基于神经网络的森吉米尔轧机板形预测模型。模型经由某钢铁公司森吉米尔20辊冷轧实测数据仿真验证表明,预测模型具有较高的预测精度。
A neural network based shape prediction model for sendizimir mill is developed and built up in light of the intrinsic weakness in the traditional shape prediction model. Computer simulation on the measured data from the 20 high sendzimir mill in one Steel Works indicates that the prediction model has higher predictive accuracy
参考文献
[1] | 前田英树ほか .压延形状制御へのフブヅィ制御の应用[J].塑性と加工(日本),1991(32):136-140. |
[2] | 中北辉雄ほか .钢铁业にすけゐ知识工学の应用[J].计测と制御(日本),1990,29(06):29-36. |
[3] | 舒迪前.预测控制系统及其应用[M].北京:机械工业出版社,1996 |
上一张
下一张
上一张
下一张
计量
- 下载量()
- 访问量()
文章评分
- 您的评分:
-
10%
-
20%
-
30%
-
40%
-
50%