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随着现代科技的发展和计算机技术的不断提高,高炉自动化操作显得越来越重要。高炉铁水硅预报能很好地反映高炉内热状态和高炉的成分,对高炉运行状态的判断起到至关重要的作用。在总结前人预报模型的基础上,综合考虑了各种影响因素,建立了BP神经网络模型,并结合现场数据进行计算,模拟结果和实际相符。
With the development of modern science and technology and continuous improvement of computer technology, blast furnace automation is more and more important. The blast furnace hot metal silicon prediction can well reflect the heat status in the blast furnace and the composition of the blast furnace, which plays a crucial role in judging the operation status of the blast furnace. On the basis of summarizing the forerunner’s forecasting model, various influencing factors are comprehensively considered, BP neural network model is established, and combined with the field data to calculate, the simulation results are in line with the actual.