级联
质量(理念)
大数据
制造工程
工艺工程
工程类
计算机科学
材料科学
冶金
数据挖掘
物理
化学工程
量子力学
作者
Xin Li,Xiaojie Liu,Ran Liu,Hongyang Li,Song Liu,Shujun Chen,Qing Lyu
标识
DOI:10.1177/03019233231221662
摘要
The sintering technology of iron and steel enterprises in China has reached a certain level. However, due to serious resource and environmental issues, how to achieve the greening of the sintering process, the intelligence of the equipment, the high quality of the products and the acceleration of the digital transformation based on intelligent decision-making and control are still key issues to be solved by the iron and steel industry. Based on the historical data of massive sintering production, this study establishes a big data platform for the whole sintering process to realise the reasonable storage and effective organisation of massive data. A sinter quality cascade prediction system, including the sinter bed permeability prediction model, burning through point (BTP) prediction model and sinter quality prediction model and a detailed software structure design are given for the application of the system. The development and application of the system are beneficial for realising the important development goals of low pollution, high yield and high quality in sinter production.
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