基于智能集成策略的烧结块残硫软测量模型

Soft-sensing model of sulfur content in agglomerate based on intelligent integrated strategy

中文关键词  软测量模型  神经网络  物料平衡  智能协调  专家规则

英文关键词  soft-sensing model  neural networks  material balance  intelligent coordination  expert rules

中文摘要

      针对铅锌冶炼烧结过程烧结块残硫估计问题,提出了一个基于智能集成策略的软测量模型,主要包括数学模型、专家规则模型和智能协调器几部分.其中数学模型通过物料平衡方程计算烧结块残硫,方程中的部分不可解参数由神经网络估计给出.专家规则模型对残硫与主要影响因素之间的关系进行了描述.基于模糊逻辑的智能协调器根据生产条件的情况综合各模型的输出作为估计结果.工业实际数据验证表明,智能集成模型的残硫估计误差平均值仅为7.5%,而且真实反映了烧结块残硫的变化趋势,可以为生产操作提供有益的指导.

英文摘要

      The parameter estimation in sintering process of plumbum and zinc smelting is a concerned challenge for the complexity in chemical reactions. The idea of intelligent integrated modeling strategy was to combine multiple modeling techniques to acquire all kinds of information from the plant. The study of estimation of sulfur content in agglomerate was vital for operation optimization. An estimation model for sulfur estimation based on intelligent integrated strategy was put forward, in which the mathematical model calculates the sulfur content in agglomerate following material balance equation with some unsolvable parameters estimated by neural network method, while the expert rule model describe the relationship between sulfur quantity and key factors. An intelligent coordinator based on fuzzy logic is proposed to synthesize the output of the models. The estimation model was tested by industrial practical data, its average error is 7.5%. So this model could be used as a guide in practical operation in sintering process.