In order to overcome the shortcomings of the traditional research method,which is only based on the theoretical modeling of the process response mechanism,a vibration early warning model of cold rolling stand based on the long short-term memory network(LSTM)algorithm is established.The accuracy and efficiency of the network warning results are also directly affected by the hyperparameters,and the validation set mean square error is selected as the objective function,and the optimal hyperparameter combination results are obtained through the grid search method of optimization calculation to construct the optimal vibration warning model.The research results show that the first volume formed intense vibration at 310s,and the second volume was located at 615s after the opening roll formed a larger peak than the first volume,which was characterized by intense vibration.With the reduction of the alarm threshold,the first volume and the second volume of the early alarm time show a monotonous increase in the law of change,in line with the actual situation.The study has good practical significance for improving the stability of the cold rolling mill.
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