Hybrid Neural Network Model for RH Vacuum Refining Process Control

A hybrid neural network model,in which RH process(theoretical)model is combined organically with neural network(NN)and case-base reasoning(CBR),was established.The CBR method was used to select the operation mode and the RH operational guide parameters for different steel grades according to the initial conditions of molten steel,and a three-layer BP neural network was adopted to deal with nonlinear factors for improving and compensating the limitations of technological model for RH process control and end-point prediction.It was verified that the hybrid neural network is effective for improving the precision and calculation efficiency of the model.

硅酸铝纤维对氧化硅陶瓷型芯性能的影响

以石英玻璃粉为原料,添加不同含量的硅酸铝纤维,通过热压注成形法制备出不同硅酸铝纤维含量的氧化硅陶瓷型芯试样,探究了不同硅酸铝纤维含量对氧化硅陶瓷型芯析晶和性能的影响规律。结果说明:随着硅酸铝纤维含量的增加,型芯试样的收缩率逐渐减小,气孔率逐渐增大,方石英含量逐渐增多,而体积密度基本不变;试样的室温和高温抗弯强度随着纤维含量的增加先增大后减小,高温挠度逐渐减小。当硅酸铝纤维含量为3wt.%时,型芯的综合性能最佳,收缩率为1.0%、气孔率为29.23%、体积密度为1.62 g/cm3、室温抗弯强度为23.36 MPa、高温抗弯强度为31.39 MPa以及高温挠度为0.69 mm。综上所述,硅酸铝纤维的加入不仅显著降低了氧化硅陶瓷型芯的收缩,还有效改善了其室温、高温抗弯强度以及高温抗蠕变性能。