CAJ | 학술논문

以传统的物料平衡和热量平衡为基础，对炼铜转炉中最新的300炉历史数据进行动态仿真，计算出吹炼过程中每隔1min的熔体主要元素组成和熔体温度，然后对之进行四次曲线拟合，将拟合出的系数作为人工神经网络的输出，优化模块中优化出的操作参数和部分原始数据作为神经网络的输入，经过训练，使之能模拟吹炼过程中的炉况变化，达到炉况监控的目的。可以通过不断增加样本数，使网络进行自学习，并组合成为炼铜转炉炉况实时预报系统。该系统成功地应用于某厂的炼铜转炉中，2000年6～10月经过四个多月的试运行，炉况实时预报系统使操作人员按系统的预报值指挥生产，各项生产指标显著提高，粗铜产量提高6.0％，冷料处理量提高8％，平均炉寿从原来的213炉至少提高到235炉，并为炼铜转炉实现在线控制提供了新思路。
이전통적물료평형화열량평형위기출，대련동전로중최신적300로역사수거진행동태방진，계산출취련과정중매격1min적용체주요원소조성화용체온도，연후대지진행사차곡선의합，장의합출적계수작위인공신경망락적수출，우화모괴중우화출적조작삼수화부분원시수거작위신경망락적수입，경과훈련，사지능모의취련과정중적로황변화，체도로황감공적목적。가이통과불단증가양본수，사망락진행자학습，병조합성위련동전로로황실시예보계통。해계통성공지응용우모엄적련동전로중，2000년6～10월경과사개다월적시운행，로황실시예보계통사조작인원안계통적예보치지휘생산，각항생산지표현저제고，조동산량제고6.0％，랭료처리량제고8％，평균로수종원래적213로지소제고도235로，병위련동전로실현재선공제제공료신사로。
Based on the material balance and heat balance，300 groups of historical data about copper converters are simulated dynamically on the computer and main element composition of a melt and the temperature in the molten bath are calculated every other one minute in the period of air refining.Then，they are fitted with quartic curve and the coefficients gotten by fitting are regarded as outputs of neural network.Partial initial data and the optimized operation parameters are considered as inputs of the neural network.Through training，the neural network can simulate the change of the furnace condition during air refining.It is able to self-study by increasing the number of new samples.It is applied to monitor the furnace condition of copper converter and constitute a real-time forecast system of furnace condition in copper converter.The system has been successfully used in operation of copper converter in a smelter.Production quota is obviously improved after running-in for four months.Copper production and the weight of cold input are increased respectively by 6.0％ and by 8.0％.Average converter life-span is improved from 213 to 235 times.A new idea has been provided for realization of in-line real-time control of copper converter.