Research on neural network model for sintering process based on iron ore characteristics
(0) A Neural Network Model ( NNM) for sintering process was investigated in this paper.According to raw material characteristics and its blending proportion in sintering plant,this intelligent model can effectively predict sintering performance indexes ( including productivity,fuel consumption,TI,particle size,,RDI and RI).Before building this Neural Network Model,it is important to understand the relationship between sintering performance indexes and iron ore characteristics.First,iron ore characteristics ( including chemical composition,physical quality,microstructure,and high temperature properties) of 41 kinds of Chinese and overseas ores were experimented.Second,70 different schemes of sinter pot tests were conducted.Third,basing on the result of the lst and 2nd steps,a software named TIBERIUS was used to build the model correlating sintering performance with iron ore characteristics.Finally,the effectiveness of the model was tested by using actual iron ore mix characteristics of a Chinese and a Brazilian steel mill.The model output predicted sintering performance indexes very close to the real production results,showing good efficiency and applicability of the model.
neural network model sintering iron ore characteristics
Dauter Oliveira WU Shengli DAI Yuming ZHANG Guoliang Alex Castro
VALE,Singapore School of Metallurgical and Ecological Engineering,University of Science and Technology Beijing,Beij VALE,China
国内会议
上海
英文
1-7
2013-06-01（万方平台首次上网日期，不代表论文的发表时间）