基于透气性预测的铅锌烧结配料过程优化研究
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摘要
铅锌烧结过程是密闭鼓风炉还原熔炼的原料准备过程,其目的是为还原熔炼提供成分合适、具有一定机械强度和还原性的烧结块。烧结配料过程是铅锌烧结生产的首道工序,是烧结炉料的准备过程。
     烧结配料过程优化是针对配料过程的两个操作参数,二配配比和混合料水分值的优化设定问题而提出的。二配配比和混合料水分值同烧结过程的状态参数透气性具有密切联系。而透气性是烧结过程的一个重要状态参数,影响着烧结生产的产量和质量。因此优化烧结配料过程对烧结生产具有重要的意义。针对烧结配料过程的二配配比和混合料水分人工调节的滞后性和盲目性的问题,探讨了基于集成预测模型与遍历优化搜索算法的配料过程优化操作方法。
     首先,从烧结过程工艺出发,详细地分析了烧结配料过程同烧结料层透气性之间的关系,同时分析了影响烧结过程透气性的一些重要因素。然后,针对烧结过程大滞后特性,采用加权组合优化方法,将基于工艺参数的BP神经网络预测模型与基于时间序列的灰色系统理论预测模型集成,建立了综合透气性集成预测模型,有效地提高了透气性状态的预测精度,为烧结配料优化奠定基础。
     在铅锌烧结配料优化过程中,直接的优化目标是烧结过程透气性,采取的优化措施是调整二配配比与混合料水分设定值。由于烧结过程透气性的优劣单由透气性预测值无法准确的表达,因此结合能够判断透气性优劣的其它一些烧结过程状态参数,利用模糊综合评判方法,来定量评价当前透气性的优劣。然后通过遍历优化搜索算法,获取最优的透气性状况评判值,进而间接获得二配配比和混合料水分优化设定值。通过仿真实验表明,该方法能够对烧结配料过程起到优化作用,同时也为铅锌烧结生产全流程协调与优化控制奠定基础。
Lead-zinc sintering process is a raw material preparation process for the reduction smelting of imperial smelting furnace, and its purpose is to provide sinter lumps which have suitable chemical compositions, certain mechanical strength and reducibility for reduction smelting. The sintering proportioning process is the first working procedure of lead-zinc sintering production, and also is the preparation process for sintering material.
     The optimization for Lead-zinc sintering proportioning process is presented in this paper, and its purpose is to solve the optimization settings issue about two operating parameters, which are values of the second proportion and the water content of mixture in the proportioning process. The values of the second proportion and the water content of mixture are close related to permeability—the state parameter of sintering process, which is very important to affect the output and quality of production. Therefore, the optimization for sintering proportioning process is of vital significance to the sintering production. Because values of the second proportion and the water content of mixture in proportioning process are regulated by manual work, have the characters of time-delay and blindness, so an optimal operating method of the sintering proportioning process based on integrated predictive model and traversing search algorithm is put forward in this paper.
     From the beginning of sintering process craft, the paper has analyzed the relationship between sintering proportioning process and permeability of sintering process in detail, and some major factors for affecting permeability. Aimed at the character of long time-delay, with the weighted combination optimal method, the integrated predictive model of synthetical permeability is established with combination of the BP neural network predictive model of the technical parameters and the grey theory predictive model of time series, which effectively improves the precision of predictive model and lays a foundation for proportioning process.
     Aiming at the permeability optimization for sintering process directly, the measure of adjusting the values of the second proportion and the water content of mixture is taken in the optimization process for lead-zinc sintering proportioning process. Whether the permeability of sintering process is optimal or inferior can not be precisely expressed by the predictive values, as a result, combining with other state parameters of sintering process which are able to judge permeability, using fuzzy comprehensive evaluation method, the paper estimated the current permeability quantitatively. Then by traversing optimization search algorithm, the best permeability evaluation value is obtained and the optimization enactment values of the second proportion and the water content of mixture are obtained indirectly. The result of simulation experiment shows that the sintering proportioning process are able to be optimized by the method, simultaneously it has prepared for coordination and optimization control for the overall lead-zinc sintering process.
引文
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