Research on Modeling Method of Cold Rolling Force Based on LSTM-JITRVM
SUN Hao1,ZHAO Ming-da1,LI Jing2,WEI Li-xin1,HU Zi-yu1
1. Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, China
2. SAIC-GM limited company Wuhan Branch, Wuhan, Hubei 043208, China
Abstract In the process of strip cold rolling, the accuracy rolling force directly affects the product quality. In order to further improve the prediction accuracy of rolling force, a rolling force model based on LSTM-JITRVM (long short term memory- just in time relevance vector machine) is proposed. Firstly, the auto-encoding network is used to extract the deep-seated features of the input data. Then the local outlier factor algorithm is used to judge whether the test sample and its neighborhood points belong to the same distribution, and different self-learning regression models are used to fit different distributions. The simulation results show that the prediction accuracy of the model can be controlled within 3%, and the rolling force can be predicted online with high precision.
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2023, Vol. 44 
