Research on Cold Rolling Force Modeling Method Based on AEGRU Network
SUN Hao1,2,YE Guo-liang1,2,ZHAI Bo-hao1,2,HU Zi-yu1,2,ZHAO Zhi-wei3
1.Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment, Yanshan University, Qinhuangdao, Hebei 066004, China
2. School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004,China
3. Department of Computer Science and Technology, Tangshan University, Tangshan, Hebei 063000, China
Abstract In the process of cold continuous rolling of steel, the prediction results of rolling force directly affect the rolling precision and product quality of strip. A rolling force model based on AEGRU (autotncoder and gate recurrent unit) network is proposed to improve the accuracy of rolling force prediction, update the model online and avoid the drift problem. First of all, the processed input data is extracted through the AEGRU network. In order to speed up the network training, the mini-batch training method is added. Then the extracted features is fitted by the Gaussian process regression model. The simulation results exhibit that the prediction accuracy of the model can be up to 3%, and the rolling force can be predicted online with high precision.
SUN Hao,YE Guo-liang,ZHAI Bo-hao, et al. Research on Cold Rolling Force Modeling Method Based on AEGRU Network[J]. Acta Metrologica Sinica, 2022, 43(9): 1172-1177.
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2022, Vol. 43 
