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铜锍P-S转炉吹炼终点复合式预报系统的开发与应用
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摘要
吹炼是火法炼铜的一个重要工序。铜锍P-S转炉吹炼是一个涉及化学反应、传热、传质、流体流动的复杂过程。其生产具有多变量、非线性、强耦合、大惯性和不确定性,吹炼过程中物料变化范围大、影响因素多,故一直难以实现实时在线控制。铜锍吹炼的产物是粗铜,防止过吹和欠吹、保证粗铜质量,是整个吹炼过程的目的和关键。因此,为了发挥铜锍吹炼P-S转炉的使用效率,尽量减少人为等不确定因素的影响,以进一步强化生产和节能降耗为目标,以“数学模拟-全息仿真-整体优化”为技术路线,开展铜锍P-S转炉吹炼优化操作智能决策与终点预报研究就显得日趋重要。
     铜锍吹炼过程优化决策的目的是为了提高劳动生产率,实现优质高产和节能降耗。为了适应生产强化的要求,更好地协调系统配置,科学地挖掘铜锍吹炼生产潜力,本文在全面研究铜锍吹炼实际生产过程的基础上,建立了铜锍吹炼过程冶金物料衡算的计算模型,对吹炼过程的粗铜产量和氧气利用率进行了理论计算;并开发了铜锍P-S转炉吹炼造铜期终点预报模型,对造铜期吹炼终点进行预测。
     在造铜期终点预报模型的开发过程中,作者综合运用两种结构不同的人工神经网络模型与经验估算方法,建立复合式铜锍吹炼造铜期终点预报系统,对造铜期吹炼终点进行辅助判断,并运用冶金物料衡算的全期氧气利用率对模型输出结果进行校验。不同学科技术的结合大大提高了模型的准确性与实用性,从而可以有效地预防或减少铜锍吹炼的质量事故,达到节能降耗,高产高效的目的;同时实现铜锍吹炼系统生产管理与优化操作的智能决策,促进了生产技术和管理水平的改善与提高。
     通过一段时间的生产实践,预报系统的预报准确率达到87%以上。该预报系统对于指导现场正常操作、保证产品质量,增加冷料处理量及粗铜产量,提高铜锍吹炼P-S转炉整体操作水平具有重要的理论意义和实用价值。
Converting is an important process in copper pyro-metallurgy. Matte converting in Pierce-Smith converters involves chemical reactions, fluid flow and transformation of both heat and mass. It is characterized by properties such as multi-variables and non-linear, couple changes with great inertia and uncertainty. Since the feeding material differs greatly and various factors will influence the process, the online control of the converting process is always the target of technicians but so difficult to realize. The product of the matte converting process is copper. The aim and key of the process are to guarantee the quality of the copper, prevent over- as well as under-converting. Hence, as to make full use of P-S converters' productivity and decrease effects of uncertain factors, it seems more and more important today to follow the technical sequence of "mathematical modeling-hologram simulation-comprehensive optimization", and to carry out research on optimization of operation and forecast of converting end-point for P-S converter, in order to further enhance production and save energy.
    The aim of optimizing decision of matte converting process is to improve productivity, achieve high quality yield and reduce energy consumption. As to meet the demands of enhanced production, to coordinate better systematic arrangement and to scientifically tap the latent power of system production, in this paper, based on comprehensive study of the industrial converting process, a mathematic model for computation of material balance of metallurgy has been set up, calculation of theoretical productivity of copper and ratio-utilized in converting process has been carried out, and the end-point forecasting system for P-S converters has been developed, to predict the end-point of the copper blow period.
    In the research, a multiplex system is set up to provide an assistant judge on the end-point of copper blow period in a converting process, in which the forecast is made based on the models of the artificial neural network and the experiential evaluation, and the result is verified with the value of the oxygen utilization ratio calculated in material balance computation. The combination of the two technologies in different subjects improves the accuracy and adaptability of the system. With help of the system to forecast the end-point of converting process, the quality accidents in matte converting will be effectively reduced and even avoided, then better energy conservation and higher productivity and efficiency will be achieved as a result. Moreover, the intelligent decision for production management and operation optimization is more likely to be brought into reality, giving an impulse on the improvement of the converting technology and managing level.
    After put into industrial application for a period of time, the forecasting accuracy of the system has been tested to be over 87%. It is also proved that the system is of important academic significance and great practical value for guiding to normal operation, guarantee of high quality production, increase in capability of dealing with cold material and productivity of copper converting, and enhancement of the whole level of operations of P-S converters.
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