【作者】 石云良；

【导师】 邱冠周； 陈淳；

【作者基本信息】 中南大学 ， 矿物加工工程， 2005， 博士

【摘要】 目前我国90%以上的能源和80%左右的工业原料都取自矿产资源,每年投入国民经济运转的矿物原料超过50亿吨。但是,随着国民经济持续发展,富矿资源日益枯竭,难采难选的矿产资源比例逐渐增加;资源的总回收率与世界先进水平相比低20%左右,堆存的尾矿既占用农田又污染环境。因此,根据高效益、低能耗、无污染的方针,充分利用现代信息技术,建立我国矿产资源开发利用的评价技术体系,充分发挥矿产资源的资源效益、经济效益、环境效益和社会效益是十分必要的。 本文分析、总结了国内外铁矿开发利用及其评价技术研究现状。采用资料检索、专家访谈和实地调查相结合的方式进行了广泛的数据收集和资料整理。以我国攀钢、包钢、酒钢、鞍钢四大重点钢铁联合企业的实际生产技术经济指标为依据作为铁矿资源开发利用评价技术研究的基础,通过收集这四大钢铁联合企业采、选、烧、冶的资源、生产技术指标等方面的详细数据,采用Matlab等软件对生产数据进行研究、分析,建立了铁精矿品位与回收率关系模型、铁精矿耗量与精矿品位关系模型、烧结矿与铁精矿品位关系模型、熔剂耗量与铁精矿品位关系模型、高炉利用系数与铁精矿品位关系数学模型。 系统地分析了铁精矿品位对选矿、烧结、炼铁等过程(简称全过程)的影响,提出了全过程铁精矿品位优化的多目标:获取的利润、铁矿石、熔剂、焦炭、电和煤的消耗等6个目标,创新地提出了成本法优化铁精矿品位的新方法,建立了各目标函数值的计算方法。所谓成本法,就是上述优化目标的权重系数采用该目标在总成本中的比例来确定,这样计算的目标函数值动态变化,更客观,更符合实际。 根据建立的数学模型,运用模糊数学的基本原理对铁精矿品位进行模糊综合评判,通过对四大钢铁公司进行了铁精矿品位的优化,其各钢铁公司的最佳铁精矿品位分别为:攀钢密地选矿厂54.0%TFe,包钢综合精矿品位64.0%TFe,酒钢综合精矿品位54.0%TFe,鞍钢调军台选厂67.5%TFe,鞍钢弓长岭选厂68.5%TFe。预测的结果正是目前组织生产或正在追求的目标。因此,该模型与实际生产取得了很好的吻合效果。 根据成本法优化铁精矿品位方法建立的专家系统,开发了基于网络服务器端(windows 2000 sever,Web服务器,SQL sever 2000,以PHP为开发语言)环境中数据库访问的先进技术,可在单机或网络下运行,以实现大范围的信息共享,形成基于网络技术的铁矿资源开发利用评价决策分析系统。 全文约5.5万字,其中含图29幅、表32张、公式10个、建立的关系模型84个。更多还原

【Abstract】 The annual consumption of various minerals used in nationwide industries in China is over 5 billions tons, and 90 percentage of energy and 80 percentage of raw materials needed originate from these minerals. While the development of the national economy continues, unfortunately, the resources with valuable elements are getting depleted, and the portion of difficult- to- treated resources is growing, and the overall recovery of the resources in China is low up to 20% in the comparison with the developed countries. Furthermore, the stockpiled tailings after the treatment occupy the farmland and pollute the surroundings. Thus, in order to fully develop the active effects of mineral resources on industrial feed, national economy, environment and society, it is necessary to build our scientific system for evaluating mineral resources utilization according to the principles of high efficiency, low energy consumption and non-pollution and with the aid of the latest information technology.The present situation of the utilization of iron ores and its evaluation systems is analyzed and summarized. The related data and papers are extensively collected by retrieving papers, enquiring relevant experts and visiting the plants. On the basis of the related industrial production data of four key iron and steel Co. (Panzhihua Iron and Steel Co., Baotou Iron and Steel Co., Jiuquan Iron and Steel Co. and Anshan Iron and Steel Co.), a number of models, such as iron recovery versus the grade of iron concentrate, consumption of iron concentrates versus the grade of iron concentrate, sinter product versus the grade of iron concentrate, consumption of flux versus the grade of iron concentrate and the utilization coefficient of furnace versus the grade of iron concentrate, are established with the help of software Matlab.After the effects of the grade of iron concentrates on the sub-processes of beneficiation, sinter and iron-making (named overall process) are systematically analyzed, it is essential that the optimization of the grade of iron concentrates for overall process (including the three sub-processes) meet the following six objectives: profits obtained and the consumptions of iron ores, flux, coke, electricity and coal. A new methodnamed ’cost method’ for optimizing the grade of iron concentrates has been put forward, which weighting factors of the above objectives depend on the cost proportion of an objective in the overall cost and can be calculated mathematically. The weighting factors are dynamically changing according to their prices fluctuations of the selected objectives. Thus the resultant value of its objective function varies and reflects its reality.The fundamentals of Fuzzy mathematics are employed for multi-object optimizations of grade of iron concentrates in overall process. It is shown that the optimal grades of iron concentrate is as follow: 54%TFe for Midi concentrate of Panzhihua Iron and Steel Co., 54%TFe for concentrate of Baotou Iron and Steel Co., 54%TFe for concentrate of Jiuquan Iron and Steel Co., 67.5%TFe for Diaojuntai concentrate of Anshan Iron and Steel Co. and 68.5%TFe for Gongchanglin magnetite concentrate of Anshan Iron and Steel Co. It can be seen that the models fit very well to the production data of the four key plants.The expert system of ’cost methods for optimizing grade of iron ores’ and its database which is based on network server (Windows 2000 sever, Web server, SQL sever 2000, and PHP language) has been developed and it can be run on a PC or a network, hence it is possible to extensively share its information and form the decision-making network system for the utilization of iron ores.更多还原