开发了较为完善的VD终点温度在线预报系统。采用MINITAB软件确定影响VD过程温降的主要因素为抽真空时间、保压时间、吹氩时间、非真空时间、VD搬入钢水的过热度、LF处理时间以及转炉出钢至VD初始测温之间的钢包运输时间。应用神经网络方法对VD处理终点的钢水温度进行在线预报，系统在线连续预报了95罐，预报温度与实际测量温度之差在±5℃范围内的比例达到937%。
The perfect VD end-point temperature on-line forecast system was established. The main factors that influenced the VD process temperature drop were found out by MINITAB software, such as pumping time, vacuum keeping time, argon-blowing time, normal time, VD original superheat degrees, LF treatment time and ladle transferring time from converter to the first temperature measurement of VD. The forecasting system was applied to forecast the VD end-point temperature on-line based on the neural network method. For continuous 95 heats, the forecast accuracy for the difference less than 5℃ between the forecasting temperature and measured temperature is up to 937%.
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