引用本文:谢书明,陶 钧,柴天佑.转炉炼钢终点磷的智能预报[J].控制理论与应用,2003,20(4):555~559.[点击复制]
XIE Shu-ming,TAO Jun,CHAI Tian-you.Intelligent method for BOF endpoint phosphorus estimation[J].Control Theory and Technology,2003,20(4):555~559.[点击复制]
转炉炼钢终点磷的智能预报
Intelligent method for BOF endpoint phosphorus estimation
摘要点击 1774  全文点击 1560  投稿时间：2001-01-10  修订日期：2002-07-12
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DOI编号  10.7641/j.issn.1000-8152.2003.4.015
  2003,20(4):555-559
中文关键词  转炉炼钢  模糊建模  遗传算法  神经网络
英文关键词  BOF steelmaking  fuzzy inference model  genetic algorithms  neural network
基金项目  国家重点基础研究发展计划973(2002cb312201); 国家自然科学基金(60074019)
作者单位E-mail
谢书明 沈阳工业大学 电气工程学院, 辽宁 沈阳 110023 xiesm@btamail.net.cn 
陶 钧 上海宝信软件股份公司, 上海 201900 neutao@etang.com 
柴天佑 东北大学 自动化研究中心, 辽宁 沈阳 110006  
中文摘要
      提出了一种用于预报转炉炼钢终点磷含量的智能方法, 在该方法中, 采用模糊推理和遗传算法, 其中模糊推理用于估算转炉熔池的磷含量, 而模糊推理模型中的各个系数则由遗传算法辨识与优化. 为了提高熔池磷的估算精度, 同时还设计了一种神经网络以补偿来自模糊推理过程的误差. 仿真结果表明了该方法的有效性.
英文摘要
      An intelligent model was introduced to estimate the bath endpoint phosphorus content for basic oxygen furnace (BOF) steelmaking. In the model, the fuzzy inference and genetic algorithms (GA) were used. The BOF endpoint [P] content was estimated by fuzzy inference model, and the parameters for the fuzzy model were optimized by genetic algorithms. For improving the precision of the endpoint estimation, an artificial neural network (ANN) was designed to compensate for the fuzzy inference error. And the simulation results show the validity of this method.