In the actual production stage,the cold rolling mill has polymorphism and time variation,so it is necessary to convert the dynamic warning of mill vibration to form a multi-variable time series warning.A vibration warning model of cold rolling mill based on LSTM algorithm was established.The results show that the early-warning performance of the model is obviously improved after the step size is increased,and the performance of the model gradually deteriorates when the step size reaches 5,and the optimal early-warning effect is obtained when the step size is 4.Combined with the actual vibration alarm threshold,vibration pre-diction is generated when the early-warning vibration energy value rises to 75%of the threshold value.The first and second volumes are predicted in advance for 1.6s and 3.2s,respectively.The research has a good guiding significance for controlling the precision of sheet metal.
Rolling mill vibrationCyclic neural network of short and long term memoryForecastModel
NETL
NSTL
万方数据
