【作者】 杨洪侠；

【导师】 孙颖；

【作者基本信息】 长春工业大学 ， 电力电子与电力传动， 2011， 硕士

【摘要】 铁合金厂是耗能大户,其生产铁合金的主要设备是矿热炉。矿热炉冶炼过程中所需能量主要来源于电能,将电能转化为热能熔化炉料。不同的炉况对电能的要求是不同的,供电制度能否满足矿热炉的用电要求,直接影响着冶炼速度、产品质量、能量消耗以及能量损耗等。因此针对不同的炉况确定合理的供电制度,提供合理的二次电压、电流值,对于铁合金厂合理控制冶炼时间,提高生产率和合金品质,实现节能降耗的目的具有重要意义。本文在查阅大量相关资料的基础上,概述了矿热炉的发展现状、发展趋势、神经网络在冶金工业中的应用以及矿热炉的机械设备、冶炼工艺和一些异常情况的处理。以中钢集团吉林铁合金股份有限公司八分厂801号炉为研究背景,对矿热炉的冶炼原理以及工艺进行分析,基于供应能量(电能和化学反应释放热能)与需求能量(消耗和损耗能量)的能量平衡建立了电能输入模型,确定了所需的总电量；基于电极位置判断矿热炉生产铁合金的三个冶炼阶段(引弧加料期、熔化期和精炼期),但是由于进入精炼期后电极位置基本不发生变化,无法准确判断精炼期的结束,所以在这里利用神经网络预测模型对精炼期的铁水温度和碳含量进行预测,当铁水温度和碳含量都满足工艺要求时,即可判断精炼期结束,即终点时刻,仿真结果验证了模型的准确性和有效性。根据各阶段不同的电能需求,分别给出电能输入方法,从理论上提出了一种新的电能输入方法：在满足单位时间供电损耗金额最小的约束条件时,确定矿热炉各个阶段的电压值,再结合各个阶段的用电量需求,得出电流值。最后利用JSP技术搭建了所提方法的能量输入优化平台。通过仿真分析,验证了所提能量输入方法能够缩短矿热炉的冶炼时间,减少消耗。为矿热炉的生产过程实现节能降耗提供了理论依据。更多还原

【Abstract】 Ferroalloy Plant is the energy-hungry factory, it’s main equipment used for producing ferroalloy is submerged arc furnace. The energy smelting process needed mainly comes from electrical energy, electrical energy is converted into heat energy to melt furnace burden. The different furnace condition needs of different electrical energy, electricity requirements in different furnace condition can be met by power supply system, which directly affect the smelting speed, product quality, energy consumption and energy losses, etc. Therefore, determination of reasonable power supply system in view of the different furnace condition, providing reasonable secondary voltage and current value, for ferroalloy plant reasonable control smelting time, increase productivity and alloy quality, to achieve the purpose of saving energy and reducing consumption has important significance.The paper on the basis of consulting a large number of relevant data and literatures, summarizes development present situation and development trend of the submerged arc furnace, applications of neural network in metallurgical industry as well as mechanical equipment, smelting process of submerged arc furnace and some treatment on the abnormal situation. With No.801 furnace of Sinosteel Jilin Ferroalloy Co., Ltd eighth branch as research background, the analysis of the smelting principle and process of the submerged arc furnace, based on energy balance on supply energy (electric energy and chemical heat release) and demand energy (consumption and wastage energy) establish the power input model, and determine the required total electric quantity; Based on the electrode position have judgment on three smelting stage of submerged arc furnace producing ferroalloy(including arc ignition、charging stage, melting stage, refining stage). But, because of the electrode position scarcely changed in the refining stage, can’t have accurate judgement of the end of the refining period, so the paper forecasting molten iron temperature and carbon content of refining period by using neural network predictive model, when molten iron temperature and carbon content meet the technological requirements, refining period is over, namely the end time. The simulation results verify the validity and the accuracy of the models. Then put forward various power input method in accordance with the electricity demand of each stage. Theoretically propose a new power input method:In meeting the constraint condition that there is the smallest loss amount in power supply in unit of time, determine voltage values at all stages of submerged arc furnace, which are combined with electricity demand of all phases, it is concluded that the current value. Lastly, the energy input optimization platform is established to realize the proposed method by JSP technology.Through the simulation analysis, validation proposed energy input method can shorten the time of smelting -arc furnace, reduce the consumption. And provide the theoretical basis for realizing that saving energy and reducing consumption in the production process of submerged arc furnace.更多还原