Edge crack damage analysis of AZ31 magnesium alloy hot-rolled plate improved by vertical roll pre-rolling

In the present study,through vertical roll pre-rolling of AZ31 magnesium alloy hot-rolled plate at room temperature,the effect of different vertical roll pre-rolling reduction on edge crack of the plate during flat rolling was systematically studied.The evolution of microstructure and texture in the edge and middle of the plate after vertical roll pre-rolling,heating and rolling was analyzed by using EBSD technology.The results show that during the vertical roll pre-rolling,{10–12}primary twins and{10–12}-{10–12}secondary twins dominated the edge deformation,while{10–12}primary twins dominated the middle deformation.With the increase of vertical roll pre-rolling reduction,the twin volume fraction of the edge and the middle increased,and the difference between them decreased gradually.After heating,the twin orientation caused by vertical roll pre-rolling was still maintained,and there was a significant difference in grain size between the edge and the middle.When the reduction rate of flat rolling was 30%,cracks have already appeared in the initial plate,while the vertical roll pre-rolled samples showed extremely high rolling performance.When the reduction rate of flat rolling was 50%,the 8PR sample still had no crack initiation.In addition,after flat rolling of 50%,the initial plate showed a strong basal texture,while the maximum pole density of the 8PR plate was small,and the texture distribution was very scattered,showing the characteristics of weak orientation.

Soft measurement model of ring's dimensions for vertical hot ring rolling process using neural networks optimized by genetic algorithm

Vertical hot ring rolling(VHRR) process has the characteristics of nonlinearity,time-variation and being susceptible to disturbance.Furthermore,the ring's growth is quite fast within a short time,and the rolled ring's position is asymmetrical.All of these cause that the ring's dimensions cannot be measured directly.Through analyzing the relationships among the dimensions of ring blanks,the positions of rolls and the ring's inner and outer diameter,the soft measurement model of ring's dimensions is established based on the radial basis function neural network(RBFNN).A mass of data samples are obtained from VHRR finite element(FE) simulations to train and test the soft measurement NN model,and the model's structure parameters are deduced and optimized by genetic algorithm(GA).Finally,the soft measurement system of ring's dimensions is established and validated by the VHRR experiments.The ring's dimensions were measured artificially and calculated by the soft measurement NN model.The results show that the calculation values of GA-RBFNN model are close to the artificial measurement data.In addition,the calculation accuracy of GA-RBFNN model is higher than that of RBFNN model.The research results suggest that the soft measurement NN model has high precision and flexibility.The research can provide practical methods and theoretical guidance for the accurate measurement of VHRR process.