シャ　キンカ   Jinhua She   佘　錦華    所属   工学部 機械工学科    職種   教授
言語種別	英語
発行・発表の年月	2014/01
形態種別	学術論文
査読	査読あり
標題	An Intelligent Integrated Optimization System for the Proportioning of Iron Ore in a Sintering Process
執筆形態	共著
掲載誌名	Journal of Process Control
出版社・発行元	Elsevier
巻・号・頁	24(1),pp.182-202
担当範囲	All
著者・共著者	Min Wu, Xiaoxia Chen, Weihua Cao, Jinhua She, and Chunsheng Wang
概要	The proportioning of iron ore is the first step of the sintering process. It mixes different kinds of iron ores with coke, limestone, dolomite, and returned sinter to produce a raw mix for the production of qualified sinter. The chemical components and proportions of the raw materials determine the chemical and physical characteristics of the resulting sinter, and thus the quality of the sinter and the amount of SO2 emissions. The prices of the raw materials and their proportions determine the price of the sinter. In this study, an intelligent integrated optimization system (IIOS) was developed for the proportioning step, which contains two phases: the first and second proportionings. First, the sintering process was analyzed, and the requirements of the proportioning step were specified. Next, an IIOS with two levels (intelligent integrated optimization, basic automation) was built. In the intelligent integrated optimization level, an intelligent integrated optimizer (IIO) produces an optimal dosing scheme. The IIO has three parts: a cascade integrated quality-prediction model, the optimization of the first proportioning, and the optimization of the second proportioning. Computational intelligence methods predict the quality of sinter. Then, the predicted quality indices are fed back to the optimizations of the first and second proportionings to find feasible optimal dosing schemes. The IIOS was implemented in an iron and steel plant. Actual runs show that the system reduced production costs by 43.014 CNY/t and SO2 emissions by 0.001% on average.
DOI	http://dx.doi.org/10.1016/j.jprocont.2013.11.012