带知识库的高炉铁水含硅量的自适应预报系统
An Adaptive System With Knowledge Base for Predicting Silicon Content in Pig Iron
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摘要: 本文讨论自校正预报器与知识库系统配合使用时,对高炉铁水含硅量的在线预报问题. 自校正预报器按Box和Jenkins的原理构成,预报模型参数用递推近似极大似然法进行在线 估计.当炉况稳定时,自校正预报器的精度是满意的,而炉况木稳定时,由知识库系统的输出 对自校正预报进行检验和修正.实验表明,综合预报系统的预报精度超过熟练工长.因此,上 述系统可作为工长的操作指导.Abstract: A self-tuning predictor and a knowledge based system are used in collaboration for predicting silicon content in pig iron for a blast furnace. It is constructed on the base of Box and Jenkin's principle. Model parameters are estimated by means of a recursive approximate maximum likelihood method. Prediction accuracy obtained by this system is much better than that obtained by an experienced operator. It can be used as an operator's guide in selecting appropriate control actions.
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Key words:
- System identification /
- knowledge-based system /
- blast furnace /
- prediction
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