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| The Aluminum Hot Strip Mill Plate Crown Soft Sensor Modeling Based on the ABC-LSSVM |
| ZHAO Xin-qiu1,2, LIU Zheng-liang1, YANG Jing-ming1,2,CHE Hai-jun1 |
1. National Engineering Research Center for Equipment and Technology of Cold Strip Rolling,Qinhuangdao, Hebei 066004, China;
2. Key Lab of Industrial Computer Control Engineering of Hebei Province,Yanshan University, Qinhuangdao, Hebei 066004, China |
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Abstract The plate crown is an important indicator of the aluminum strip in Aluminum hot strip mill flatness control. In order to accurately predict the aluminum hot strip mill plate crown,a soft sensor model was established on the base of artificial bee colony (ABC) and least squares support vector machine (LSSVM) . ABC was applied to the process of the model parameters optimization because prediction accuracy and generalization ability of LSSVM model depends on the choice of the parameters. The prediction performance of the model was tested by sample data collected at the scene of a factory 1+4 aluminum hot rolling. The model was compared with Marquardt and the LSSVM model whose parameters were optimized by Genetic Algorithms(GA).The simulation result shows that the ABC-LSSVM soft sensor model parameters optimization fast, simple structure and high precision .
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［1］ 王伟,陈殿生,魏洪兴,等. 装载机载重测量的支持向量机软测量建模方法［J］.计量学报,2008,29(4):329-333.
［2］ 胡伟.基于反馈BP网络的铝热连轧板凸度预报建模［J］.计算机与现代化,2011,(11):11-14.
［3］ 吴德会.基于最小二乘支持向量机的传感器非线性动态系统辨识［J］.计量学报,2008,29(3):226-230.
［4］ 顾燕萍,赵文杰,吴占松.最小二乘支持向量机的算法研究［J］.清华大学学报(自然科学版),2010,50(7):1063-1066.
［5］ 李文莉,李郁侠.基于粒子群最小二乘支持向量机的水文预测［J］.计算机应用,2012,32(4):1180-1190.
［6］ 周辉仁,郑丕谔.基于GA和Bootstrap的最小二乘支持向量机参数优选［J］.系统仿真学 报,2008,20(12):3293-3296.
［7］ Johan V R, Hedwig V, Rainer M. Accurate profile and flatness control on a modernized hot strip mill［J］. Iron and Steel Engineer,1996,73(2) : 29-33．
［8］ Deng S,Tsung-Han Yeh. Applying least squares support vector machines to the airframe wing-box structural design cost estimation［J］. Expert Systems with Applications, 2010, 37(12): 8417-8423.
［9］ Karaboga D, Basturk B. A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm［J］. Journal of Global Optimization, 2007,39 (3): 459-471.
［10］ 曹文平,李伟华,王利鑫,等.人工蜂群算法在飞轮充电控制系统中的应用研究［J］.华东电力,2011,39(9):1500-1504.
［11］ 于明,艾月乔.基于人工蜂群算法的支持向量机参数优化及应用［J］.光电子·激光,2012,23(2):374-378. |
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2014, Vol. 35 
