Research on cascade intelligent sinter quality prediction system based on big data technology

Abstract

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.